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Special Issue on ‘EU PVSEC 2024: State of the Art and Developments in Photovoltaics’,
edited by Robert Kenny and Gabriele Eder
ORIGINAL ARTICLE
Failure mode analysis of Austria’sfirst road-integrated
photovoltaic system
Alexander Erber
*
and Bernhard Grasel
Competence Field Renewable Energy Technologies, University of Applied Sciences Technikum Vienna, 1210 Vienna, Austria
Received: 30 June 2024 / Accepted: 28 October 2024
Abstract. The exploration of traffic areas as a novel photovoltaic integration opportunity within the traffic
sector, specifically in road surfaces, has been demonstrated in various projects. Limited data and publications
about the performance and failure modes of these innovative road-integrated modules highlights the need for a
comprehensive failure analysis. This study focuses on first time assessing failure modes of road-integrated
photovoltaic modules installed at Austria’sfirst road-integrated PV system in Teesdorf. A comprehensive failure
mode analysis is conducted at the 100 m
2
PV parking place using a combination of quantitative and qualitative
methods. These methods include regular visual inspections, I-V-curve measurements at both string- and
module-levels (with a simplified STC correction), electroluminescence- and dark-I-V-curve measurements, and
the use of monitoring data. The PV parking place produced 10.2 MWh in its first operation year, 27.18% less
than the estimated yield. Visual inspections reveal various failure modes, including detachment of the module
top layer, delamination, and broken module edges. In the analysed monitoring data continuous power losses are
observed over the systems operation time. String-level power losses of up to 47.8% (mean: 33.5%) are calculated
for the first year of operation. For the second year of operation the power losses reach a up to of 77.5% (mean:
56.2%). Cell cracks as the main cause of these power losses, attributed to vehicle loads, are identified through
electroluminescence images. Out of 16 analysed strings with dark I-V-curve measurements three showed at least
one bypass diode malfunctions. The combination of quantitative and qualitative methods identified multiple
failure modes and their main causes. As a conclusion, the study highlights the challenges of integrating
PV modules into road surfaces, emphasizing the need for standardisation and quality assurance in the field of
road-integrated PV applications.
Keywords: Road-integrated photovoltaics / maintenance / reliability / failure mode analysis /
I–V curve measurements / dark I–V curve / electroluminescence
1 Introduction
The yearly installed photovoltaic (PV) capacities of the past
two years show high two-digit growth rates in the European
market, with 42% in 2022 and 43 % in 2023 [1]. In the Austria
market more than half of the cumulative capacity in 2023
were installed in those two years [2]. With the first time
achieving 1 GWp of added capacity in 2022 and the highest
growth rate in Europe in 2023 (+157.96%), Austria is on
track to achieve the Renewable Energy Act goal of 13 TWh
electricityfromPVaheadof the 2030target[3], althoughnew
studies for Austria show that in order to reach climate
neutrality by 2040 21 TWh of PV are necessary by 2030. The
high installation capacities challenge not only the aspect of
grid integration. It further saturates the predominant
rooftop market in Austria (84% in 2022 and 86% in
2023 [2]). For yearly PV installations in the range of
1-2 GWp new potentials need to be tapped. Besides the
ground-mounted PV systems where the social acceptance in
Austria is lower (54% [4]) than for roof-top and building-
integrated PV (BIPV) systems (81%), other PV potentials
and system types must be considered. Compared to other
renewableenergytechnologiesPVmodulescan be integrated
into existing structures, facilitating a synergistic and
combined area utilization for new PV potentials. Key
integration options include building-integrated PV, Agri-
PV, and floating PV. The exploration of traffic areas as a
novel integration opportunity within the trafficsector,
especially in road surfaces, bike- and walkways, has been
demonstrated in various projects worldwide since 2006
[5–10] and discussed in the literature [10–13]. Beside
prototypes [14–17] and experimental research approaches
[9,18,19], companies, such as Solar Roadways, Wattway by
Colas, SolaRoad, Platio Solar, developed products for the
broad application of this PV integration type. Although
*e-mail: alexander.erber@technikum-wien.at
EPJ Photovoltaics 15, 42 (2024)
©A. Erber and B. Grasel, Published by EDP Sciences, 2024
https://doi.org/10.1051/epjpv/2024038
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which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
some publications focus on the durability and robustness of
these products and prototypes, limited data on failure modes
are available. In Coutu et al. [20] the durability and
robustness of the Solar Roadways module was evaluated
without analysing the influence of the applied load cycles on
the electrical performance. The research in Ma et al. [15]isa
further example for this. For demonstrations projects
constructed with SolaRoad modules the results of visual
inspections are discussed in [21]. In Klerks et al. [22] the yield
and the performance of the first solar bike ways in the
Netherlands is analysed. Although different failure modes
such as delamination or degradation of the anti-skid layer
and the improvement of the used product versions are
discussed, no further failure analysis methods (e.g. current-
voltage(I-V)curve measurement,electroluminescence(EL),
etc.)areapplied.Inthe“RollingSolar”project[23] crystalline
silicon and thin-film module (copper indium gallium selenide
CIGS) were analysed in an controlled environment with
mechanical stress of passing cars. The efficiency losses were
calculated and validated with accelerated lab tests, but no
further methods to analyse possible cell cracks in the field
(e.g. with EL or UV fluorescence) were conducted. EL was
used in Colberts et al. [24] for the feasibility assessment of
thin-film PV laminates for road integration in an laboratory
environment,where smallersampleswere usedforthetesting
approach. In general all publication stating yield values of
road-integrated PV systems [22,23] show that there are
power losses over the course of the operating time that are
higher than the usualdegradation rates and can therefore be
attributed to failure and degradation modes.
The mentioned publications show the lack of data on
failure modes of road-integrated modules (RIPV), or in
general traffic area-integrated modules, in the field. Those
results would be especially valuable for the scientific
community to develop improvements for RIPV applica-
tions and for planners and stakeholders to evaluate the
technology in terms of its market maturity.
In this paper, the focus is on assessing the failure modes
of RIPV modules installed at Austria’sfirst RIPV system
in Teesdorf. The PV parking place undergoes a compre-
hensive failure analysis using a combination of quantitative
and qualitative methods. These methods include regular
visual inspections, I-V curve measurements at string- and
module-levels, EL and dark-I-V-curve measurements, and
the use of monitoring data. The comprehensive approach
allows the identification of failure modes, the quantification
of their performance impact, and determines or narrows
down the causes. Through the participation in the planning
phase, a distinction can be made between causes of errors
due to system planning problems and product errors.
Finally, possible improvements for the analysed PV
module are formulated and the suggestions for the whole
field of RIPV are derived from the results.
2 Material and methods
In this section, first an overview of the analysed RIPV
system in Teesdorf is given, including the construction of
the systems. Afterwards, the measurements setups, the
data processing and analysis steps are described.
2.1 PV parking place Teesdorf
The PV parking place in Teesdorf (Austria) was
commissioned in May 2022 on an already existing parking
place in front of the community centre in Teesdorf (see
Figs. 1a and 1b). The location was chosen due to the fact
that the parking lot for the public building is mainly used in
the evening when different kinds of events take place.
During daytime, the parking lot is only used rarely and
allows the area to be utilised for photovoltaic power
generation during that time. From a research point of view,
this is an attractive constellation as the performance during
daytime and the vehicle loads during nighttime can be
investigated at one location.
For the construction of the site, the existing pavement,
together with the substructure, was removed and replaced
by a concrete foundation. Plastic profiles were then
mounted on the foundation, and the PV modules were
placed on top of them (see Fig. 1c). The profiles were
mounted with according spacing, so that every module had
contact with three profiles (one on each edge and one in the
middle) for a better load transfer to the concrete
foundation. This allowed an easier cable management
and enables the placement of sensors below the modules
after commissioning.
The whole systems consist of 780 commercially
available four cell RIPV modules, with a load capacity
of two tonnes according to the manufacturer. Each
module has a nominal power of 21.52 Wp and consists
of a glass-foil assembly on the top and a polymer
composite substructure. Further module data is presented
in Table 1. The module does not have a certification
according to IEC 61215. To reach the operating voltage
rang of the used IQ7+ Enphase
®
microinverters [25]the
modules were connected to strings of 18 to 20 modules. In
the layout of the string plan factors such as shading due to
nearby buildings and possible parking cars, the inverter
input parameters and safety parameters (OVE E 8101
[26]) were considered. The connection of the modules in
the strings was made through 3M
TM
Scotchlok
TM
MGC
connectors. Each of the 42 strings is connected to one
IQ7+ microinverter. Figure 1d shows the string layout
with the labelling of the strings and the number of
modules in one string.
The production of the RIPV system is used in the
nearby community centre and the surplus is fed into the
public grid. Besides the inverter monitoring no further
continuous monitoring of the strings is carried out. To
differentiate between mechanical and weather induced
material degradations a reference string of 20 modules is
placed on the roof of the community centre. Further there
is a datalogger on the community centres roof to log
weather data (irradiation, air temperature, relative
humidity and wind speed) and measure the backsheet
temperature of three RIPV modules. The backsheet
temperature is used for analysing the temperature
behaviour of the RIPV module under test. The reference
string and datalogger are in operation since October 2023,
due to problems with the logger hardware. Further details
about the PV parking place in Teesdorf are described
in [27].
2 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
Table 1. Module data of the analysed RIPV module.
Dimension (H WD) 353 353 41 mm
Technical data
Glass thicknesses/module structure •6 mm tempered glass (anti-slip R12)
•Encapsulant-Cell-Encapsulant-Backsheet
Weight 6.5 kg
Number of bypass diodes / Cells 1/4 monocrystalline cells
Material of the module substructure Recycled polymer composite; LDPE and
HDPE copolymer with matrix-forming material
Maximum load (wheel load) 2000 kg
Electrical data
MPP power P
MPP
21.52 Wp
MPP voltage U
MPP
2.29 V
MPP current I
MPP
9.39 A
Open circuit voltage U
oc
2.68 V
Short-circuit current I
sc
9.85 A
Temperature coefficients
P
MPP
,U
oc
,I
sc
–0.38%/°C, 0.32%/°C, 0.05%/°C
Connection cable 2.5 mm
2
(blank without plug)
Fig. 1. PV parking place in Teesdorf (Austria); (a) top view of the PV parking place, (b) side view with the community centre
Teesdorf in the back, (c) dimensions and layer structure and (d) string layout of the RIPV system with string labelling (The first digit in
the labelling code referees to the inverter boxes, which each contain 21 microinverters, and the last two digits are the sequential
numbering of the strings).
A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024) 3
2.2 Failure mode analysis
The comprehensive failure modes analysis of this study
uses quantitative and qualitative methods, which are well
described in the literature [28–30]. This combination of
methods enables the quantification and location of failure
modes. Figure 2 provides an overview of the methods used
and the possible types of failure modes that can be
detected.
Qualitative methods are referred to in this study as
analysis methods where no information about the electrical
state or behaviour of the analysed modules or strings are
obtained. Visual inspection (see Sect. 2.2.1), electrolumi-
nescence (EL) (see Sect. 2.3), the measurement of the dark
I-V curve (see Sect. 2.3.1) and the signal transmission
method (see Sect. 2.3.2) are used as qualitative methods in
this study. As mentioned in IEC TS 60904-13 [31] and
demonstrated in Kropp et al. [32] EL can be used as a
qualitative method as well. The same applies to the
measurement of the dark I-V curve, where the resistances
and the other parameters of the one- or two-diode-model
can be determined by analytical evaluation [30].
To quantify the influence of the detected failure modes
the following quantitative methods are used: I-V curve
measurements on module- and string-level (see Sect. 2.2.2)
and the analysis of the monitoring data (see Sect. 2.2.3).
In the following subsections, each conducted method-
ology of the above-mentioned failure mode analysis
methods is described, covering the measurement setup
and measurement procedure through to data preparation
and analysis. The analysis period of the failure mode
analysis ranges from May 2022 to June 2024.
Thermography is not used for the analysis, as captured
thermography images where to blurred for a proper
analysis, due to the glass thickness of 6 mm (see Tab. 1).
Further, EL is an alternative (detecting the same and more
failure modes) for field thermography, although with the
cost of longer setup times and the need of more equipment
(DC supply, camera, laptop). UV fluorescence is not used
in this study, because due to the short timespan between
commissioning and a test measurement in October 2023 no
useable UV fluorescence was found, as the method would
require more UV exposure during the day [33].
2.2.1 Visual inspection
Visual inspections at the PV parking place in Teesdorf are
carried out at regular intervals (2-3 months) or in response
to messages from the monitoring system. Anomalies and
defects are documented using visual images and the module
position in the system. Inspection checklists, as the one
developed in Köntges et al. [28], are not used, as they are for
normal PV modules and considering the number of
modules (780) the data that can be gathered using a
checklist is not in reasonable proportion to the time
required. Inspections carried out by the system owner
(municipality of Teesdorf) are also included in the analysis.
The recorded image material is analysed together with
the module position in the system to be able to assign
visually detected faults to local or material-related causes.
Furthermore, in combination with the quantitative
methods, it is also analysed whether the detected failure
modes have an influence on the performance of the modules
and the string or are purely material degradations.
2.2.2 I-V curve measurements
To quantify changes in module performance, the I–V
curves of selected modules were measured after the systems
commission in May 2022 and after the first year of
Fig. 2. Overview of the applied failure mode analysis methods and their detectable failure modes or analysis parameter (quantitative
methods). The numbering of the individual methods represents the order in which they are described in the methodology and results
sections.
4 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
operation in May 2023. As the voltage range (up to 2.6 V) of
modules (see parameters in Tab. 1) is too low for
conventional I-V curve measurement devices, the modules
of a string are measured in accordance with IEC 60904-1
Ed.3.0 under standard test conditions (STC) conditions in
aflasher at the Austrian Institute of Technology (AIT) in
Vienna. The selected string is string 2.40, as it is assumed
that it will be exposed to frequent vehicle loads during its
operating time due to its location close to the community
centre entrance. The measurements are carried out in a
pulsed sun simulator (multiple flash method) of class A+A+
A+[34–36]. The initial characterisation of string 2.40 and the
reference modules of the roof system took place on 4
th
May
and 5
th
May 2022. After the first year of operation the
characterisation of the string 2.40 modules took place on 23
rd
May2023.The referencestringmoduleswere not measuredas
the rooftop system had not yet been installed at this time and
were therefore not exposedto any weather-related influences.
After the first year of operation, I-V curve measure-
ments for all strings are carried out on the test site on 22
nd
May 2023. The I-V curve measuring device HT I-V-400 is
used for this purpose. An on-site measurement after
commissioning was not possible as the device was in repair
and calibration at the time. As the module rear side
temperature cannot be measured due to the module design,
the temperature on the front side of the module is recorded.
The PT100 sensor is attached to a module from string 2.16
for the I-V curve measurements (a module from string 2.15
was used to measure string 2.16). The PT100 is shielded
from direct sunlight to prevent a temperature increase
caused by the irradiation.
Where results from both I-V curve measurements are
shown (flasher and on-site), the reference to indoor and
outdoor measurement are added to enable a better
differentiation.
Figure 3 shows the evaluation steps for the I-V curve
measurements, including input data and analysis steps.
The test reports of the measurements at the AIT are
evaluated with regards to the Maximum-Power-Point
(MPP) power of the modules, compared with the data
sheet value and the deviations are analysed. Based on the
change in module output, the degradation rates of the
measured modules in the first year of operation are
calculated. Furthermore, the module’s I-V data, provided
by the AIT, is imported and procced in Python. The raw
measurement current-voltage data is averaged over 500
data points, new curve points at uniform current values are
calculated for all module I-V curves using interpolation.
The module I-V curves of string 2.40 are combined to string
I-V curves for the years 2022 and 2023 with the addition of
the module voltage values at the same current value. This
enables a qualitative analysis of the string I-V curves and
the calculation of the degradation rate of string 2.40.
The string characteristics measured with the HT I-V 400
(excel file) are processed as well in Python. In the first step a
simplified STC correction is performed for the string I-V
Fig. 3. Flow chart of the data processing and evaluation steps of the I-V curve measurements. The numbering corresponds to the order
the steps are a carried out.
A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024) 5
curve of string 2.40and graphi graphically validated with the
string I-V curve of the AIT measurement for the year 2023.
The STC correction applied is described in the following
Section 2.2.2.1. After validation of the simplified correction
method, the STC correction of all measured string I-V curves
is performed. This is then used to validate the simplified STC
correction applied to the monitoring data.
2.2.2.1 I-V curve measurements at the PV parking place
and simplified STC correction
As the correction methods described in IEC 60891 [36]
*
cannot be used for the STC correction, a simplified STC
correction of the measured string I-V curves is carried out
basedontheinfluencing factors on the I-V curve given by
(1) and (2). It considers the temperature dependency of
the module’s voltage and the linear influence of irradiation
on the current. The corrected voltage values U
n_C
are
calculated with the voltage values of the measured I-V
curve U
n_M
, the temperature coefficient of the open
circuit voltage a, the measured module temperature Tand
the STC temperature T
STC
. For the calculation of the
corrected current values I
n_C
the measured current values
I
n_M
, the short-circuit current of the measured I-V curve
I
SC_M
, the measured irradiation E
M
and the STC
irradiation E
STC
are used. If the short-circuit current
were replaced by the term of the respective current value
I
n_M
, the correction would not consider the irradiation
dependence of the voltage. The influence of temperature
on the current is neglected. Finally, the MPP of the
respective string is determined using the STC-corrected
string I-V curve.
Un C ¼Un M
1þa⋅TTSTC
ðÞðÞ
ð1Þ
In C ¼ISC M ⋅
ESTC
EM
1
þIn M :ð2Þ
2.2.3 Monitoring data analysis
The monitoring data analysis is carried out in several steps
and uses further data sources in addition to the inverter
monitoring (Enphase
®
Enlighten
®
). The process is shown
in Figure 4.
First, the necessary meteorological data for the analysis
is collected and processed in Python. As no weather station
was installed at the car park in Teesdorf at the time the
system was commissioned, weather data (global radiation,
air temperature) from the GeoSphere Austria weather
station closest to the system location is used. The data of
the weather station in Gumpoldskirchen (∼10 km distance
to the RIPV system) is exported from the GeoSphere
Austria Data Hub [37].
In the second step the data of the inverter monitoring is
exported, collected and processed for all 42 strings in the
period from 12
th
April 2022 to 30
th
June 2024. As the DC
parameters do not have constant recording intervals (less
than 15 min) average values over 15 min are calculated and
Fig. 4. Flow chart of monitoring data analysis. The numbering corresponds to the order the steps are a carried out.
*
The correction parameters for methods 1, 2 and 4 are not known
and cannot be calculated due to only one recorded I-V curve per
string. Method 3 requires the measurement of several I-V curves
and is therefore also not applicable for this work.
6 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
used to determine the DC power. The DC parameters
correspond to the MPP parameters (MPP current and
MPP voltage) of the strings. Then clear-sky days are
selected in the observation period. These are needed for the
trend analysis of the string power values over time and
the application of the STC correction. The selection is
made by filtering the power data days with exclusively
positive power gradients up to 12:00 p.m. and validated
via visual data inspection. The string used for this filtering
is 1.1, as this has the least shading in the winter months and
little shading from vehicles is assumed. The performance of
all strings on the clear sky days is then analysed for
deviations and anomalies.
As it is expected that RIPV modules have a different
temperature behaviour than standard PV modules (slower
behaviour due to higher heat capacity and no rear
ventilation) and no backsheet temperature for the parking
place modules are recorded, a stationary one-parameter
temperature model is developed. Measurement data from
the validation period of the measurement hardware is used
for this. The measurement setups and the used hardware
components are described in [27]. The measurement data
(global radiation E
Global
, module backside temperature
T
Module
and air temperature T
Amb
) is exported from the
data logger and imported into Python for data processing.
The observation period is the month of September 2023. As
with the monitoring data, clear-sky days are determined
based on the global radiation for the next evaluation steps
by visual data inspection. The selected days are then
displayedgraphicallyin a scatter plot (T
Module
T
Amb
onthe
ordinate and E
Global
on the abscissa). A linear regression
curve is determined for a specified period of the day (at least
until 12:00). The parameters (slope kand offset d) of the
regression curve are used to create a radiation-dependent
stationary temperature model according to (3).
TModule ¼TAmb þk⋅EGlobal þd:ð3Þ
With the created temperature model, the GeoSphere
Austria weather data and the monitoring data, an STC
correction of the power maxima on the determined
monitoring clear-sky days is carried out according to (4).
It should also be noted that the global radiation maximum
E
M_max
is not calculated at the same time as the MPP
power maximum P
MPP_M
, as local differences (distance
between GeoSphere Austria weather station and car park)
can result in deviations (local shading by clouds, etc.). The
temperature coefficient of the MPP power gis shown in
Table 1.
PMPP STC ¼
PMPP M ⋅
ESTC
EM max
1þg⋅TModul TSTC
ðÞðÞ
:ð4Þ
The STC-corrected string power values are then
validated with the power values of the STC-corrected
string I-V curves and power values of the calculated string
I-V curve of string 2.40 (based on the AIT module
measurements). The last step is the analysis of the
evolution of the string powers over the analysis period.
2.3 Electroluminescence
Night-time electroluminescence (EL) measurements are
carried out on 9
th
May 2022, 15
th
May 2023 and 2
nd
October
2023 to analyse possible cell cracks and contacting
problems at the RIPV modules and to determine short-
circuited bypass diodes. The MBJ Mobile EL from MBJ
Solutions is used as the measuring system for this. The
system consists of a camera (silicon detector) with a frame,
a power supply unit and a laptop with a control and
analysis software. The voltage and current range of the
power supply is 0 to 60 V and 0 to 25 A.
Due to the mounting frame and field of view of the
camera only four to six of the PV modules are captured in
one EL image. This means that up to four individual
images are required to capture an entire string EL image.
The reverse current is not selected in accordance with IEC
TS 60904-13 [31] (reverse current with I
SC
and 0.1 I
SC
),
as it is not possible to set this current value for strings with
long cable lengths due to the voltage limitation of the
power supply unit. Instead, the reverse currents are set
individually. The same thing applies to the exposure time,
which is determined separately on each measurement day
using test images and is adjusted during the individual
recordings.
For the evaluation, the individual EL images are
combined in the GIMP image processing software to create
string and complete system EL images. In the final step, the
EL images are analysed qualitatively (occurrence of cell
cracks and their development over time, interconnection
problems at the solder connections and identification of
short-circuited bypass diodes).
2.3.1 Dark I-V curve measurements
A self-build measurement setup consisting of a current
sensor (LEM CKSR 15-NP [38]), a voltage sensor (LEM
DVC 1000-P [39]) and a measuring device (MonoDAQ-U-X
[40]) is used to measure the dark I-V curves. The
DewesoftX software (installed on a laptop) is used for
data acquisition. The string under test is connected with
the measurement box and a regular laboratory DC power
supply. The DC supply used has a voltage and current
range of 0 to 60 V and 0 to 5 A.
The dark I-V curve measurement was carried out
together with the last EL measurement on 2
nd
October
2023. The dark I-V curve is recorded from the reverse bias
quadrant to forward bias quadrant by manually changing
the voltage value on the power supply unit.
The measurement data is recorded at a sampling rate
of 10 kHz and averaged over one second for evaluation. In
the next step, the I-V curve data is exported as an excel
file. Afterwards the files are then imported into Python,
displayed graphically and analysed qualitatively. Possible
bypass diode faults are identified by higher reverse
voltages with the same reverse current in a relative
comparison to the other strings. Short-circuited bypass
diodes can be detected by lower voltages in the forward
bias quadrant.
A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024) 7
2.3.2 Signal transmission method
If open circuit problems occur during the analysis period
the signal transmission device pvTector from photo-
voltaikbuero [41] is used for locating the open circuit
position. The method works with two different frequency
signals [30] injected in the open circuit string at both poles
in reference to ground. With a receiver the injected signals
are converted to audio signals. Then the string under test is
examined with the receiver. Where the audio signal
switches frequency the open circuit position is found.
3 Results
This section describes the results of the failure mode
analysis. The failure modes determined by the applied
analysis methods are explained and assigned to their
possible causes. The results of the quantitative methods
(I-V curve measurement and analysis of the monitoring
data) are used to quantify the effects of failure modes in
terms of power losses. Based on the results of the qualitative
methods (visual inspection, EL and dark I-V curve
measurement) the causes or possible causes of all detected
failure modes are described.
3.1 Visual inspection and signal transmission method
The main failure modes found through visual inspection are
presented in Figure 5. Three months after the systems
commissioning, at some glass-foil modules detachments
from the module substructure and break outs at the module
edges were observed. This allowed water to enter the room
between the glass-foil module and the substructure. The
observed material degradations are not linked to a decrease
in system or string power for the first year of operation.
However, a connection with power losses due to module and
cell short circuits was found in the second year (see Sect.
3.4). In addition to the detachment of the glass-foil modules
and the broken edges, visually flawless modules also
showed water ingress between the module glass and the
module edges, as the seals on the module edges had come
loose (only visible under very close inspection). These
water ingresses were detected by a person walking over the
modules.
As the inspections progressed, an increased occurrence
of delamination at the module edges were detected. In
conjunction with the material defects described above, this
ledto the replacement of 34 moduleson 9
th
August2022. Two
modules of string 2.40 were replaced in this process as well.
On 7
th
February 2023, two modules with broken glass
were detected by the municipality of Teesdorf. No
correlation between the modules position in the system
and the defect type were found. Vandalism was assumed
to be the cause of the two glass breakage modules.
A surveillance camera had not yet been installed at the
parking place at this point. However, due to the renewed
occurrence of the failure mode in January 2024, a
temperature-related cause in connection with the ingress
of water freezing and subsequent vehicle loading could
not be ruled out. Due to a camera malfunction renewed
vandalism must also be considered.
In addition to the increasing number of modules with
edge delamination, modules with already existing edge
delamination showed an increase in the delaminated
module area. Recognisable delamination above the cell
surfaces (see Fig. 5.) indicates that the delamination is
between the glass and the encapsulation. The delamination
can be attributed to several possible causes. Firstly (1),
delamination is favoured or caused by not optimally
selected lamination parameters (temperature and pres-
sure) [42]. Secondly (2), delamination could be favoured by
the detachment of the glass-foil module from the module
substructure possible connection between the delamina-
tion at the module edges and the adhesive points. The third
(3) possible cause is the stress caused by the vehicles during
acceleration and braking. As these forces are not absorbed
directly by the module frame and transferred to the module
substructure via the glue point, the possible displacement
of the module layers can reduce the adhesion to the
neighbouring materials (cell, glass or backsheet) and cause
delamination.
The breaking off of the module edges is primarily
attributable to insufficient material thickness. In addition,
the UV resistance of the substructure’s copolymer material
and missing expansion joints must not be disregarded as a
further cause or accelerating influence. The latter men-
tioned is due to a planning error where the thermal
expansion of the modules was not considered.
Fig. 5. Main material degradations found during visual inspections: Detachment of the top layer (glass-foil-module) from the base
structure (left), delamination at the module glass edges (middle) and broken module edges (right).
8 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
As already mentioned, the material degradations
progressed further or even accumulated in some modules
(detachment, edge breakage and delamination). In June
2024, modules were discovered in which the mechanical and
electrical connection to the substructure was interrupted
and the modules were therefore no longer connected to the
strings. These modules had broken edges in common and
the most plausible cause of disconnection of the electrical
wiring is due to horizontal vehicle forces (e.g. braking or
acceleration).
During the operation time of the system two strings
(2.42 and 2.41) went out of operation and an open circuit
problem was identified as the cause of the failure. Through
the signal transmission method, it was possible to locate
the open circuit positions (Fig. 6). Crushed cables caused
the open circuit due to ether wrong installation or the
thermal movement of the PV modules over time.
3.2 I-V curve measurements
Figure 7 shows the measured outdoor I-V curve, the STC
corrected string I-V curve and the calculated string I-V
curve based on the AIT measurements in 2023 of string 2.40
(indoor). The MPP power of the STC corrected string I-V
curve is 244.10 W and deviates 2.94% from the MPP power
of the AIT string characteristic curve (237.12 W). The
qualitative comparison of the two STC curves shows a
match of the characteristic curve in the MPP range,
whereby the STC corrected I-Vcurve lies above the AIT I-V
curve. Since the deviation of the MPP power is in the range
of the measurement uncertainty of the I-V-400, the
simplified STC correction was applied to all measured string
characteristics.
The deviation of the AIT I-V curve from the STC
corrected string I-V curve at lower string voltages, which
does not affect performance, can be explained by faulty
bypass diodes in the modules of string 2.40. As a result, the
weakest module limits the string power at lower voltage
values. This was not considered when creating the I-V
curve based on the AIT measurements. No extrapolation
was carried out for the STC-corrected characteristic curve
in the open-circuit voltage range, as this was not required
for validation.
Figure 8 shows the validation of the monitoring data
STC correction with the STC-corrected MPP powers of the
string I-V curve measurement (outdoor). For this purpose,
Fig. 6. Detected open-circuit positions at string 2.42 (left) and string 2.41 (right) with the signal transmission method.
Fig. 7. Validation of the simplified STC correction of the string I-V curve measurement (outdoor) of string 2.40 with the calculated
string I-V curve from the AIT module measurements (indoor).
A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024) 9
one clear-sky day before and after the string I-V curve
measurement is used. Further the MPP power of the
combined string I-V curve from the indoor I-V curve
measurements at the AIT is added. With an average
deviation (I-V curve vs. monitoring data) of 2.1% (21 May
2023) and 1.5% (25 May 2023), it can be stated that the
simplified STC correction is valid. However, it should be
noted that there are deviations of up to 9.5% (overestima-
tion) specific to the strings, which must be considered when
analysing the results.
The results of the module I-V curve measurement at the
AIT are shown in Figure 9 based on the MPP power. After
commissioning, the modules of string 2.40 have a maximum
output power that deviates from the data sheet (21.52 Wp)
with an average of 16.25 Wp (T_2022) and are 24.5%
below the manufacturer’s specifications. The same can be
seen for the modules of the reference system (R_2022) with
an average output of 16.74 Wp (–22.2%). The measure-
ments of the string 2.40 modules after one year (T_2023)
show a further reduction in output power to an average of
Fig. 8. Validation of the STC corrected monitoring data with the STC corrected string I-V measurements (outdoor) and the AIT
measurement (combined string I-V curve; indoor) based on the string MPP powers.
Fig. 9. Measured MPP power of the modules (indoor measurement) of string 2.40 (T_2022 and T_2023) and the reference string
modules (R_2022) compared to the data sheet value. Power values with the uncertainty range of the measurement device [35,36].
10 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
12.94 Wp (–39.9% compared to the data sheet value),
whereby the outputs are more widely distributed (16.20
Wp to 9.40 Wp). Only three of the modules (5, 12 and 15)
show no power losses when the measurement uncertainty is
considered. A further analysis of the I-V curves is carried
out in [27].
Based on the two measurements in 2022 and 2023, the
degradation rate of the string 2.40 modules can be
estimated at an average of 20.4% for the first year of
operation. The fluctuation range is 1.6% to ‒43.7%.
Figure 10 shows the string I-V curves of string 2.40,
which were calculated from the module I-V curves of the
two AIT measurements (2022 and 2023). The string MPP
power is 323.01 W after the system commissioning and
237.12 W after one year of operation. This results in a
degradation rate at string level of 26.6%. The difference to
the average module degradation rate of 20.4% can be
explained by the current limitation of the weakest module.
Considering the slope of the 2023 I-V curve at I
SC
and the
steps in the region of I
SC
the drop in the filling factor,
compared to the 2022 I-V curve, is attributed to cell cracks
(drop of parallel resistance) (see Sect. 3.4) and delamina-
tion (see Sect. 3.1). With I-V curve measurements power
losses can be calculated, but a clear assignment to failure
modes sourly on I-V data is not possible for all detected
changes in the curves slope. Therefore, I-V curve measure-
ments should be combined with other failure analysis
methods (thermography, EL, etc.). For Figure 10, one
could assume that failure modes affecting the series
resistance, such as solder corrosion, homogeneous soldering
disconnections or broken cell interconnect ribbons [28], are
present, due to the slight change in the slope at V
OC
.
Although with EL (see Sect. 3.4) and visual inspections
those modes can be ruled out. The slight change in the slope
at V
OC
and the reduction of V
OC
is influenced by a low
parallel resistance due to the cell cracks. With increasing
cell cracks and inactive areas this change in the I-V curve
will increase.
3.3 Monitoring data analysis
In the first year of operation, the yield of the PV parking
place is 10.2 MWh (spec. 100 kWh/m
2
), which corre-
sponds to a deviation of 27.14% from the expected yield of
14MWh(calculatedthroughsimulationinPV*Sol
®
Premium). The reason for this deviation is due to the
reduced module power compared to the data sheet value
at the time of installation and further power degradations
during the first year of operation. Figure 11 shows the
increasing deviation of the correlation between irradiation
and PV power (AC) in spring 2023. The figure also shows
the timestamps of the conducted measurements, failures
and module replacements. Due to a power share of 2.5%
(based on the number of modules), the failures of string
2.41 and string 2.42 are not visible. The failure causes of
string 2.41 and 2.42 were identified through the
measurement of the open circuit voltage. As explained
in the previous section the open circuit positions were
found with the signal transmission device.
The measurement results in the form of the
irradiation-related module temperature increase
(T
Module
T
Amb
) as a function of the global radiation
for six September days (clear-sky days) are shown in
Figure 12. In addition to the temperature behaviour of
the RIPV module, the temperature behaviour of a
regular PV module is illustrated. The temperature
behaviour of the standard module can be described by a
straight line with an origin near the zero point (offset of
approx. 2.5 °C). The reasons for the deviation of the
regression curve from the intersectionpointatthezero
point are the short period for modelling and the
scattering of the measurement data due to the cooling
influence of the wind.
The temperature behaviour of the RIPV module shows
a time-dependent curve compared to the standard
module. Further it is shown that the RIPV module has
a lower temperature till 650 W/m
2
due to the higher heat
Fig. 10. String I-V curves of string 2.40 (calculated from the module I-V measurements at the AIT) for 2022 and 2023 (both indoor
measurements).
A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024) 11
capacity. At over 650 W/m
2
, the temperature of the RIPV
module rises above the temperature of the regular module
as there is no rear ventilation. The temperature rise of the
RIPV module in the morning shows a higher gradient than
the temperature decline in the afternoon. This indicates
that the heat capacity of the module must be considered
when developing a temperature model for an annual
simulation of RIPV systems. However, as the temperature
model in this work is only used for the simplified STC
correction, the temperature behaviour in the afternoon is
not considered further.
A linear regression curve was calculated for the period
from 9:40 to 13:15. The calculated parameters of the
regression curve were used to create the temperature
model. As the curve does not originate at the zero point, it
is assumed that the module temperature corresponds to the
air temperature for radiation values below 450 W/m
2
.
Figure 13 illustrates the development of the STC-
corrected module-normalised power (string power per
module) over the RIPV systems operation time. The use
of the module-normalised power is necessary to make the
string powers comparable due to the different string lengths.
Fig. 11. AC power output of the PV parking place. Global radiation of the weather station in Gumpoldskirchen and marked time
events (green = operating time, red = string outages problems, black = measurements).
Fig. 12. Temperature behaviour of the analysed road-integrated PV module (RIPV) and a regular (reg.) module from 09:40 to 16:00.
Regression curves for both modules and the regression parameters of the temperature model for the RIPV module.
12 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
Furthermore, string values with module-normalized power
below 2 W are not shown for better clarity, as strings with
these values can be considered non-functioning at that time.
In comparison to Figure 11, a reduction in power can
already be seen in September 2022, which continues until
the end of the observation period. The string powers show
an increasing spread over the operating time. The
correlation between string position in the system and
power reduction is also recognisable here strings that
are in middle of the systems or closer to the municipality
centre degrade faster as more cars park there. The
fluctuations and outliers in the power curves are due to
soiling, self-cleaning by rain and the developed tempera-
ture model. Based on the monitoring data, the average
power losses of the strings in the first year of operation
(comparison of 31
st
May 2022 with 28
th
May 2023) are
33.5% with a spread of 13.8% to 47.8%. For the second
year of system operation (comparison of 31
st
May 2022
with 16
th
June 2024) average power losses of 56.2% with a
spread of 29.2% to 77.5%. However, 18 strings were no
longer in operation on 16
th
June 2024, as the string voltage
was below the starting and operating voltage of the
inverters.
3.4 Electroluminescence
The EL images of the on-site measurements carried out in
May 2022, May 2023 and October 2023 are shown in
Figure 14. For a detailed analysis, the EL images of string
2.40 are presented in Figure 15. It must be stated that a
comparison between the strings (e.g. comparison of the
local series resistances) is not possible due to the different
reverse currents [27]. For the classification of cell cracks the
modes explained in Köntges et al. [43] and IEC TS 60904-13
[31] are used.
In the EL image of 2022, the modules show differences
in the local series resistance evident through the contrast
differences in the module and string. These contrast
differences are due to contacting problems at the soldering
points (modules 2, 3, 5, 9, 12, 15 in Fig. 15). Furthermore,
cell cracks of type A are visible (modules 3, 4, 5 and 8 in
Fig. 15). As the first EL image was taken approximately
one month after commissioning, the cell cracks may have
occurred either during module production or in the first
month of operation.
The EL image of May 2023 confirms cell cracks and
cell fractures as the main cause of the power losses.
A comparison of the images (May 2022 with May 2023)
shows a significant increase in cell cracks and cell fractures.
Most cell cracks can be classified as type B and type C, with
type C cell cracks being the most frequent. Modules with
cell cracks or cell fractures show almost the same fracture or
crack pattern diagonal cracks with active cell areas at the
outer cell edges. Based on the repeating patterns, the cause
of the cell cracks and cell fractures are attributed to the
vehicle load and the inadequate support of the glass-foil
module by the substructure of the analysed module. In
addition to modules where all four PV cells show diagonal
cracks, there are also modules with only one to three affected
cells. The reason for this could be a difference in wafer/cell
quality [44] or an asymmetrical load on the modules (e.g.
vehicle tyres only apply load to the edge of the module).
The possible development of the cell cracks over time
can be seen in module 5 in string 2.40: Starting from a semi-
circular continuous crack at the outer cell corner, finer cell
cracks and cell fractures occur over time, which move
towards the centre of the module.
In addition to the cell cracks, short-circuited cells in
strings 1.2, 1.27 and 2.38 and short-circuited modules in
strings 1.28 and 2.38 are seen (October 2023) in Figure 14.
Fig. 13. Evolution of the STC corrected string powers (shown as module-normalised power) on the selected clear-sky days.
A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024) 13
Short-circuited cells occur when both cell poles are
short-circuited by moisture due to delamination. At
module level, the cause also appears to be due to water
ingress between the glass-foil module and the module
substructure, where the bypass diode is located. The
outage of 18 strings in June 2024, due to too low voltage,
shows that the number of short circuits (module or cell)
increased in the second year of operation.
The strings with the least cell cracks are string 1.1, 1.2
and 1.3, which are located on the side of the cable ducts and
are the furthest away from the entrance to the community
centre. It must therefore be assumed that cars were park
less frequently in these parking places compared to other.
The inactive cell areas of the EL image of string 2.40
from May 2023 in Figure 15 show a high correlation with
the MPP power data in Figure 9. Two modules (modules
12 and 15) in string 2.40 are noticeable, with no
recognisable cell cracks until October 2023. The situation
is similar for other strings. A lower mechanical load on
these modules can be ruled out with a high degree of
certainty due to the cell cracks in the neighbouring
modules.
The EL image of string 2.40 (Fig. 15) shows that there is
only a slight increase in cell cracks between May 2023 and
October 2023. Modules 2, 3, 6, 7, 11, 14, 16, 17 and 19 of
string 2.40 show no or marginal changes in the crack
Fig. 14. EL images of the PV parking place in May 2022 (top), May 2023 (middle) and October 2023 (bottom) with string label.
14 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
pattern. This further indicates that the power losses after
October 2023, shown in Figure 13, are due to cell and
module short-circuits.
3.5 Dark I-V curve measurement
The dark I-V curves of the measured strings in October
2023 are shown in Figure 16. Out of the 16 strings
(reference string excluded), which represent 40% of the
strings functioning at this time, two (string 2.36 and 2.30)
show no current flow in the forward direction. The reason
for this is attributed to temperature-related contacting
problems in the modules. No power deviations of the
affected strings in relative comparison to the other strings
during daytime and the enabling of a current flow due a
mechanical load during the measurement of string 1.28
support this assumption.
Furthermore, faults due to open bypass diode paths are
visible in the dark I-V curves. The affected strings 1.2, 2.35
and 2.40 have flatter reverse I-V curve compared to the
other strings. The number of modules with an open bypass
diode path per string cannot be calculated due to the
unknown reverse I-V curve of the tested modules. For the
remaining strings, including string 2.36 and 2.30, no bypass
diode fault is detectable. Assuming that all measured
modules are installed with functioning bypass diodes, the
open bypass diodes are due to water ingress behind the
glass-foil module and the electric wiring of the bypass
diode. Furthermore, thermal overload due to a lack of rear
ventilation cannot be ruled out.
In addition to the string dark I-V curves of PV parking
place, the dark I-V curve of the reference string with
20 modules (Ref. string) is shown in Figure 16. In the
reverse voltage quadrant, this string shows the diode
characteristic of 20 passive bypass diodes (pBD), which
have higher voltage drops than the active bypass diodes
(aBD) installed in the rest of the RIPV modules.
As Figure 16 shows strings with different numbers of
modules and therefore faults in the forward bias quadrant
are more difficult to recognise, Figure 17 illustrates strings
with 18 modules. A buckle in the dark I-V curve of string
1.28 (orange) is recognisable, which is due to an electric arc.
Fig. 15. EL images of string 2.40 in May 2022 (top), May 2023 (centre) and October 2023 (bottom). The numbering corresponds to the
module numbers in Figure 9. Replaced modules are marked in red.
A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024) 15
The affected module could not be localised as the arc was
not visually detectable during the measurement. The
affected area in the module is initially non-conductive at
low voltages and becomes conductive at higher voltages
due to the arc. Second, a voltage difference can be seen at
string 2.38 and 1.28 (overlap of the dark I-V curves)
compared to the remaining strings with 18 modules. This
voltage difference is caused by one short-circuited module
in each string. Due to the low open-circuit voltage of
the modules and the number of 20 bypass diodes in a string,
the exact identification of a module short-circuit is difficult
without the inclusion of an EL image.
4 Discussion
The results of the failure mode analysis at the PV parking
place in Teesdorf show that several analysis and measure-
ment methods are required for a comprehensive failure mode
analysis to quantify the effects of failures and identify the
their causes. The I-V curve measurement and the analysis of
the monitoring data are suitable as quantitative methods for
determining power losses at system, string or module level. By
using visual inspections, electroluminescence and dark I-V
curve measurements as quantitative methods, it is possible to
localise faults and determine the causes of faults.
Fig. 16. Dark I-V curves of all measured strings at the PV parking place (x.xx) and reference string (ref. string). The abbreviation in
brackets refers classifies the present bypass diode type in the strings (aBD = active bypass diode, pDB = passive bypass diode).
Fig. 17. Dark I-V curves of all measured strings with 18 modules.
16 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
The visual inspection method has proven to be
advantageous compared to data collection using a
checklist, as it enables more time-efficient data collection.
A disadvantage is the lower level of detail of the
information per module compared to a checklist and
consistency problems when different parties carry out the
inspection. In the case of PV modules for road-integration,
however, it can be assumed that faults will occur more
frequently due to the module design, the choice of
components or the type of installation. These can be
analysed more time-efficiently by classifying the fault
types. Therefore, the level of detail per module of visual
inspections can be kept low at the beginning of application-
orientated testing of new PV modules. In the further stages
of development, the level of detail should be increased. The
combination with other failure analysis methods (I-V curve
measurement, EL, etc.) is recommended before increasing
the level of detail, as not all types of failure modes can be
detected with visual inspection (e.g. cell cracks, bypass
diode problems).
Regarding the used quantitative methods, it must be
mentioned that the calculated power losses and degrada-
tion rates at string level are subject to uncertainties. For
example, the simplified STC correction of the string I-V
curves and monitoring data represents a possible uncer-
tainty, as not all factors influencing a PV I-V curve were
considered. This can be seen from the varying deviation of
the string power of both data sources in Figure 8. The short
measurement period (one week) of the created temperature
model must also be considered as an uncertainty. It is not
possible to precisely quantify the uncertainties of the data
from the string I-V curve measurement and the monitoring
system due to the simplifications made. However, uncer-
tainty quantification would provide little additional benefit
due to the extent of the calculated power losses, and as the
power degradation of strings progresses over time, the
modules no longer fulfil their purpose sufficiently and must
be replaced under the manufacturer’s warranty.
The EL imaging carried out at the PV parking place
made it possible to identify cell cracks and cell fractures as
the main cause of the power losses. Regarding the choice of
reverse currents for the EL imaging, a standardised return
current for all strings would have enabled a string
comparison. This should be considered for future measure-
ments at the PV parking place.
The dark I-V curve measurement was used to identify
three open bypass diode paths and two short-circuited
modules in 16 measured strings. Short-circuited modules
are easier to be identify in the dark I-V curve compared to
the daylight I-V curve as no temperature differences are
present between the modules at night. The low open-circuit
voltage of the PV module under test (2.68 V) nevertheless
represents a certain scope for misinterpretation compared
to a standard PV module. Recording the dark I-V curve
with standardised current values could reduce this and
would enable software-supported detection.
With open bypass diode paths, there is a risk of hotspots
with damaging effects on the cells. This risk increases when
close shading by vehicles is considered. As thermography
was not used in the failure analysis due to assumed blurred
images stemming from the glass thickness, no correlation
between the local heat generation and open bypass diode
was analysed in this study. Nevertheless, the local heat
generation due to close shading should be analysed in
future work on RIPV module and could be helpful in the
optimization of shade resistant module designs.
5 Conclusions
The RIPV module used at the parking place in Teesdorf is
comparable with other available RIPV modules in terms of
cell technology (monocrystalline silicon) and module
structure (thickness of the module components, which
absorbs the mechanical loads). Differences may arise from
the type of integration into the traffic area (adaptation vs.
integration), the material of the cover layer (glass vs.
synthetic resin). Nevertheless, it can be assumed that the
main findings of this work (delamination, cell cracks and
bypass diode problems) can be transferred to other RIPV
systems, considering the module structure (glass-glass or
glass-foil), the module components and the vehicle loads to
which the modules are exposed. For validation purposes,
the transferability of the results of this work can only be
verified based on further comparable analyses on other
RIPV systems.
Both material degradation (detachment of the glass-foil
module from the module substructure, delamination and
module edges breaking away) and power degradation were
found at the RIPV system. The material degradations
could not be directly linked to the determined performance
reductions, but the detachment of the glass-foil module
together with the breaking module edges allowed water to
enter the module. This water ingress was identified as the
main cause of module short circuits and open bypass diode
paths. The main cause of the power losses is due to cell
cracks and cell fractures (inactive cell areas) caused by the
vehicle loads.
Using the example of the modules of string 2.40
(measurement in accordance with IEC 60904-1), it was
determined that the modules had an on average 24.5%
lower power at the time of commissioning than specified in
the manufacturer’s data sheet. With the correlation
between the indoor and outdoor I-V curve measurements,
all installed modules had lower power than specified at the
datasheet. Through this finding it can be stated that the
manufacturer’s quality inspection is inadequate and
requires a more comprehensive final inspection. It is
therefore recommended that end customers choose RIPV
modules with certification or extractable test certificates in
accordance with IEC 61215. However, this does not
guarantee the quality of every produced module but proves
that the modules submitted to the testing institute meet
the test requirements. Furthermore, the accelerated ageing
tests can detect certain types of failure modes during the
test. The delamination problem of the tested RIPV
modules could possibly have been detected by the thermal
cycles, the heat/humidity and UV tests in accordance with
IEC 61215. An adaptation of the IEC test is required for the
mechanical load test, as RIPV modules are exposed to
higher static and dynamic loads. It should also be
considered that the stresses are primarily caused by vehicle
A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024) 17
tyres. Compared to wind loads, these tyres have a smaller
force area. In addition, braking and acceleration activities
cause a further force and direction of force. The inclusion of
traffic engineering tests in the test sequence, such as slip
resistance tests or other resistance tests for traffic surfaces,
should also be considered.
Due to the low number of installations and projects
compared to other types of PV integration (BIPV, floating
PV or agricultural PV), an international, European or
national standard for the component approval of road-
integrated PV modules is not foreseeable in the next five to
ten years. As the drafting of standards and the development
of testing infrastructure are influenced by the demand for the
respective products and the size of the product market.
In addition to improving quality control, further
suggestions for improving the RIPV module can be
formulated based on the findings of this work. To prevent
cell cracks and cell breakage, a change in the module design
is necessary, as this led to the highest power losses at the
solar car park in Teesdorf. If the module design is retained
by the manufacturer, the maximum load capacity should
be reduced. Changing the module design from a glass-foil
module to a glass-glass module would result in better
mechanical stability for the PV cells. In addition, the cells
would be positioned in the neutral axis in a glass-glass
module under bending stress and would therefore
be exposed to less mechanical stress. When switching to
glass-glass modules, the lamination parameters must also
be optimised to prevent delamination due to incompletely
cross-linked encapsulation. To improve the temperature
behaviour, a filling material other than air is recommended
between the RIPV module and the substructure, as this
would enable a cooler cell temperature and better module
performance. At the same time, the filling material could
also improve the force transmission through the module.
A further aspect that could be considered in a possible
redesign of the RIPV module is the change in cell
technology. Compared to crystalline silicon, thin-film
technologies on flexible carrier materials would withstand
the mechanical vehicle stresses without cell cracks. This
would also enable resource and cost savings (e.g. through
lower glass thicknesses).
The results and findings of this paper show that various
types of failure modes occur in RIPV or generalised as
traffic area-integrated PV systems in the form of material
and power degradations. Using the example of the modules
examined at the PV parking place in Teesdorf, significant
power losses were found, which highlight the challenges of
integrating PV modules into road surfaces. Further
research on degradations modes and module stability as
well as standardisation in module testing are required for
the development of RIPV.
Acknowledgments
The authors wish to express their sincere gratitude to Mr. David
Warren for his valuable contribution to proofreading this article.
His assistance in refining the language and clarity of the
manuscript is greatly appreciated.
Funding
This research was funded by the Austrian Climate and Energy
Fund (Project number C177537), for which we would like to
express our sincere thanks. The APC was funded by the
University of Applied Sciences Technikum Vienna.
Conflicts of interest
The authors declare no conflict of interest.
Data availability statement
The data that support the findings of this study are available from
the corresponding author upon reasonable request.
Author contribution statement
Conceptualization, A.E. and B.G.; Methodology, A.E.; Software,
A.E.; Validation, A.E. and B.G.; Formal Analysis, B.G.;
Investigation, A.E.; Resources, A.E.; Data Curation, A.E.;
Writing Original Draft Preparation, A.E.; Writing Review
& Editing, B.G.; Visualization, A.E.; Supervision, B.G.; Project
Administration, A.E.; Funding Acquisition, A.E. All authors
have read and agreed to the published version of the manuscript.
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Cite this article as: Alexander Erber, Bernhard Grasel, Failure mode analysis of Austria’sfirst road-integrated photovoltaic
system, EPJ Photovoltaics 15, 42 (2024)
20 A. Erber and B. Grasel: EPJ Photovoltaics 15, 42 (2024)
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