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Applications – Transportation | Battery, hybrid electric vehicles—Trucks and buses: And I would drive 500 miles—With batteries?
With growing demands to save greenhouse gases, the rapid market introduction of battery-electric trucks (BETs) will become increasingly important, with truck manufacturers announcing various models entering the market in the near future. Soon, truck operators will be faced with deciding which battery capacity and cell chemistry to choose in their next purchase. In this study, we evaluate the choice of battery capacity, regarding feasibility and cost-effectiveness, for trucks using NMC and LFP cell chemistry. Our results show that higher energy density allows larger NMC batteries to be installed, resulting in the ability to transport higher payloads at low charging powers. The LFP chemistry has to rely on higher charging powers of up to 700 kW to transport the same payloads. When asked to choose a battery capacity for the individual use case, the smallest battery size should always be selected when only charging powers up to 300 kW are available. However, the reduction in publicly charged energy can lead to cost advantages of larger battery capacities at higher charging powers. When deciding between the two cell chemistries, the LFP chemistry shows advantages in most cases. Only at high payloads and low charging powers the NMC chemistry shows cost advantages.
The eco-efficiency assessment compares diesel, battery electric, and hydrogen powered heavy-duty vehicles. Therefore, a life cycle costing is combined with a life cycle assessment. These models calculate the vehicles’ costs and environmental impact on a cradle-to-grave perspective. The results show that battery electric and hydrogen powered vehicles potentially outperform the status-quo diesel vehicles in both objectives.
The decarbonization of the transport sector, and thus of road-based transport logistics, through electrification, is essential to achieve European climate targets. Battery electric trucks offer the greatest well-to-wheel potential for CO2 saving. At the same time, however, they are subject to restrictions due to charging events because of their limited range compared to conventional trucks. These restrictions can be kept to a minimum through optimal charging stop strategies. In this paper, we quantify these restrictions and show the potential of optimal strategies. The modeling of an optimal charging stop strategy is described mathematically as an optimization problem and solved by a genetic algorithm. The results show that in the case of long-distance transport using trucks with battery capacities lower than 750 kWh, a time loss is to be expected. However, this can be kept below 20 min for most battery capacities by optimal charging stops and sufficient charging infrastructure.
With the rise of battery electric vehicles to mass production, many technical improvements have been realized to drastically increase the electric range, efficiency, and sustainability. However, insights into those valuable state-of-the-art solutions are usually not shared with researchers due to the strict non-disclosure policies of electric vehicle manufacturers. Many studies, therefore, rely on assumptions, best-guess estimates, or insider knowledge. This article presents an in-depth multi-scale analysis of the electric powertrain characteristics of a Volkswagen ID.3 Pro Performance. The focus is set on the range, power, and lifetime perceivable by the user. Thorough experimental tests are performed from the battery cell to vehicle level, following the energy conversion from source to sink. Energy densities are determined at all levels and the absolute electric range is quantified under varying operating conditions. Power capability is evaluated at cell level by quantifying the battery cell and pack performance with current rate tests in charge/discharge scenarios and impedance determination, as well as by determining powertrain energy conversion efficiency with in-vehicle measurements. Moreover, accelerated aging tests of the lithium-ion battery cells are performed with close to real-world conditions and projected to vehicle level, demonstrating that the lithium-ion battery pack achieves mileages outperforming the warranty information of the manufacturer under real-world operation. Overall, the results provide valuable insights into the current state of the art and can serve as a reference for automotive engineering in academia. Over 10 GB of lithium-ion battery cell, pack, and overall powertrain measurement data from the lab and real-world environment is available as open source alongside the article.
The launch of both battery electric vehicles (BEVs) and autonomous vehicles (AVs) on the global market has triggered ongoing radical changes in the automotive sector. On the one hand, the new characteristics of the BEV powertrain compared to the combustion type have resulted in new central parameters, such as vehicle range, which then become an important selling point. On the other hand, electric components are as yet not optimized and the sensors needed for autonomous driving are still expensive, which introduces changes to the vehicle cost structure. This transformation is not limited to the vehicle itself but also extends to its mobility and the necessary infrastructure. The former is shaped by new user behaviors and scenarios. The latter is impacted by the BEV powertrain, which requires a charging and energy supply infrastructure. To enable manufacturers and researchers to develop and optimize BEVs and AVs, it is necessary to first identify the relevant parameters and costs. To this end, we have conducted an extensive literature review. The result is a complete overview of the relevant parameters and costs, divided into the categories of vehicle, infrastructure, mobility, and energy.
The advancement of electric mobility as a measure to comply with international climate targets and sustain renewable resources in the future has led to an electrification of the mobility sector in recent years. This trend has not been spared in the logistics and commercial vehicle sector. Emerging electric powertrain concepts for long-haul vehicles have since been developed and adapted to different use cases and axle concepts. In this paper, the authors show the influence of the powertrain topology and the associated design of the electric machine on the efficiency and energy consumption of commercial vehicles. For this, existing series or prototype long-haul axle topologies are analyzed regarding their efficiency and operating points within four driving cycles. Additionally, a sensitivity analysis on the influence of the total gearbox ratio tests the assumed designs. We find that single-machine topologies offer efficiency advantages over multiple-machine topologies. However, this study highlights a joint consideration of application-specific machine design and topology to realize the full technological potential.
Electrification and automation are attracting interest from the public-transportation sector for their potential to improve energy efficiency, cost efficiency, and environmental performance. Singapore is planning to integrate autonomous buses/minibuses into its transportation system by 2030. However, before the island-wide deployment of autonomous vehicles, there is a need to evaluate their effects on sustainability. A study was therefore conducted in Singapore to evaluate the costs and environmental impacts of autonomous electric minibuses, and the results are revealed and discussed here. This paper presents a case study to demonstrate the impacts of replacing human-driven diesel buses with electrified and automated minibuses on life-cycle costs and greenhouse gas (GHG) emissions for seven routes. The vehicles evaluated were a 12‑m human-driven diesel bus, a 6‑m electrified human-driven minibus, and a 6‑m electrified autonomous minibus. First, the impacts of the vehicle concepts on the scheduling were analysed to obtain the operational strategy and passenger occupancy along the route. A life-cycle assessment (LCA) and a total cost of ownership (TCO) analysis were then conducted to compare the fleet-level costs and GHG emissions. The results showed a 43% reduction in total life-cycle cost for the autonomous electric minibus, compared with the 12‑m diesel bus. The life-cycle GHG emissions of the 6‑m autonomous electric minibus were also reduced by 47% compared with the 12‑m diesel bus, despite the fact that a larger number of the former vehicle were required in the fleet.
The transportation sector needs to significantly lower greenhouse gas emissions. European manufacturers in particular must develop new vehicles and powertrains to comply with recent regulations and avoid fines for exceeding CO2 emissions. To answer the question regarding which powertrain concept provides the best option to lower the environmental impacts, it is necessary to evaluate all vehicle life-cycle phases. Different system boundaries and scopes of the current state of science complicate a holistic impact assessment. This paper presents a scaleable life-cycle inventory (LCI) for heavy-duty trucks and powertrains components. We combine primary and secondary data to compile a component-based inventory and apply it to internal combustion engine (ICE), hybrid and battery electric vehicles (BEV). The vehicles are configured with regard to their powertrain topology and the components are scaled according to weight models. The resulting material compositions are modeled with LCA software to obtain global warming potential and primary energy demand. Especially for BEV, decisions in product development strongly influence the vehicle’s environmental impact. Our results show that the lithium-ion battery must be considered the most critical component for electrified powertrain concepts. Furthermore, the results highlight the importance of considering the vehicle production phase.
Powertrain system design optimization is an unexplored territory for battery electric trucks, which only recently have been seen as a feasible solution for sustainable road transport. To investigate the potential of these vehicles, in this paper, a variety of new battery electric powertrain topologies for heavy-duty trucks is studied. Thereby, topological design considerations are analyzed related to having: (a) a central or distributed drive system (individually-driven wheels); (b) a single or a multi-speed gearbox; and finally, (c) a single or multiple electric machines. For reasons of comparison, each concurrent powertrain topology is optimized using a bilevel optimization framework, incorporating both powertrain components and control design. The results show that the combined choice of powertrain topology and number of gears in the gearbox can result in a 5.6% total-cost-of-ownership variation of the vehicle and can, significantly, influence the optimal sizing of the electric machine(s). The lowest total-cost-of-ownership is achieved by a distributed topology with two electric machines and two two-speed gearboxes. Furthermore, results show that the largest average reduction in total-cost-of-ownership is achieved by choosing a distributed drive over a central drive topology (−1.0%); followed by using a two-speed gearbox over a single speed (−0.6%); and lastly, by using two electric machines over using one for the central drive topologies (−0.3%).
The pivotal target of the Paris Agreement is to keep temperature rise well below 2 °C above the pre-industrial level and pursue efforts to limit temperature rise to 1.5 °C. To meet this target, all energy-consuming sectors, including the transport sector, need to be restructured. The transport sector accounted for 19% of the global final energy demand in 2015, of which the vast majority was supplied by fossil fuels (around 31,080 TWh). Fossil-fuel consumption leads to greenhouse gas emissions, which accounted for about 8260 MtCO2eq from the transport sector in 2015. This paper examines the transportation demand that can be expected and how alternative transportation technologies along with new sustainable energy sources can impact the energy demand and emissions trend in the transport sector until 2050. Battery-electric vehicles and fuel-cell electric vehicles are the two most promising technologies for the future on roads. Electric ships and airplanes for shorter distances and hydrogen-based synthetic fuels for longer distances may appear around 2030 onwards to reduce the emissions from the marine and aviation transport modes. The rail mode will remain the least energy-demanding, compared to other transport modes. An ambitious scenario for achieving zero greenhouse gas emissions by 2050 is applied, also demonstrating the very high relevance of direct and indirect electrification of the transport sector. Fossil-fuel demand can be reduced to zero by 2050; however, the electricity demand is projected to rise from 125 TWhel in 2015 to about 51,610 TWhel in 2050, substantially driven by indirect electricity demand for the production of synthetic fuels. While the transportation demand roughly triples from 2015 to 2050, substantial efficiency gains enable an almost stable final energy demand for the transport sector, as a consequence of broad electrification. The overall well-to-wheel efficiency in the transport sector increases from 26% in 2015 to 39% in 2050, resulting in a respective reduction of overall losses from primary energy to mechanical energy in vehicles. Power-to-fuels needed mainly for marine and aviation transport is not a significant burden for overall transport sector efficiency. The primary energy base of the transport sector switches in the next decades from fossil resources to renewable electricity, driven by higher efficiency and sustainability.
The use of heavy-duty battery electric trucks for long-haul transportation is challenging because of the required high energy amounts and thus the high capacity of traction batteries. Furthermore a high capacity battery implies high initial costs for the electric vehicle. This study investigates the required battery capacity for battery electric trucks considering the requirements of long-haul transportation in Germany and compares the life cycle costs of battery electric trucks and conventional diesel trucks in different transportation scenarios. The average consumption is simulated for different battery electric truck configurations on the main German highways and transportation scenarios incorporating battery charging during driver rest periods. The results show that in average case the required battery would restrict the payload to only 80% of a usual diesel truck payload that might be acceptable considering the statistical payload use. The life cycle costs in the examined scenarios also considering the charging infrastructure show that battery electric trucks can already perform on the same costs level as diesel trucks in certain scenarios.
The new Megawatt Charging System (MCS) standard will enable battery electric trucks (BETs) to recharge
a large share of their battery during mandatory rest periods in the EU. We investigated the impact of this
new standard on the required battery size and the cell properties required to reach functional parity with
a diesel truck (DT) for various operation strategies. EU truck driving regulations allow a one-stop operating
strategy, in which a truck can be charged during the mandatory 45-minute break following 4.5 h of driving.
In addition, we analyze the impact of additional charging stops and relaxing EU regulations by allowing free
distribution of rest durations. For the one-stop operating strategy, we find that a charging power of at least
761 kW is needed to match the operating patterns with a 798 kWh battery. Higher charging powers are only
beneficial in terms of downsizing the battery if multi-stop-strategies are deployed. In our scenarios, a charging
power of 2802 kW is the highest beneficial charging power, which is significantly lower than the proposed
MCS standard and suggests that the maximal charging power of 3.75MW in the MCS standard is oversized
for the long-haul truck application. The resulting cell requirements for achieving package capability, payload-,
lifetime and total cost of ownership (TCO) parity demonstrate that multi-stop-strategies benefit from a smaller
battery size in terms of cell price, volumetric and gravimetric energy density, but pose higher requirements
on C-Rate, charging power and cycle stability. State of the art automotive cells are close to reach the required
gravimetric and volumetric energy densities, but need to improve their cycle stability.
During a period of 7 months, 54 class N3 trucks from 4 fleets of German fleet operators were equipped with high resolution GPS data loggers. A total of 1.26 million km of driving data has been recorded and constitutes one of the most comprehensive open datasets to date for high-resolution data of heavy commercial vehicles. This dataset provides metadata of recorded tracks as well as high-resolution time series data of the vehicle speed. Its applications include simulation of electrification for heavy commercial vehicles, modeling logistics processes or driving cycle construction.
To reach cost-parity with diesel trucks, battery-electric trucks require fast-chargeable lithium-ion cells with a high energy density and cycle life, at a low specific cost. However, cells generally excel at only a fraction of these characteristics. To help select the optimal cell, we have developed the techno-economic cell selection method. The method determines the price per kilowatt-hour that is required to reach cost-parity with a diesel truck, based on the characteristics provided in a cell’s datasheet. We demonstrate the method by selecting the optimal cell out of a database containing 160 cells for a long-haul truck operating with a single driver in Germany in two scenarios: charged at 350 kW and charged at 1 MW. The results show that for trucks charged at the current maximum charging power of 350 kW, the cell price needs to drop to ca. €60 kW⁻¹ h to reach cost-parity with a diesel truck. When 1 MW charging power is available, cost-parity can be reached at a cell price around €100 kW⁻¹ h, which is within reach of optimistic cost estimates. However, the most cost-effective cells require more volume and result in a lower maximum payload than a diesel truck. A parameter sensitivity analysis shows that best-in-class cell energy density and packaging efficiency are required to match the payload capacity and powertrain volume of a diesel truck. The cell cycle life, cost of charging and vehicle energy consumption have the biggest impact on the cost-effectiveness of battery electric trucks.
Despite fast technological advances, world-wide adaption of battery electric vehicles (BEVs) is still hampered—mainly by limited driving ranges and high charging times. Reducing the charging time down to 15 min, which is close to the refueling times of conventional vehicles, has been promoted as the solution to the range anxiety problem. However, simply increasing the charging current has been known to accelerate battery aging disproportionally, leading to severe capacity and power fade while posing an unacceptable safety hazard during operation. Many different approaches have been taken to develop new fast charging strategies for battery management systems to solve the dilemma between charging speed and battery aging. To date, there is no consensus on how to optimally determine a fast and health-aware charging strategy. From an application-oriented perspective, the questions arise of what the advantages and disadvantages of the various methods are and how they can be applied. This article presents a comprehensive review and novel approach for classification of over 50 studies in fast charging strategy determination of the state of the art. We evaluate and compare all studies according to the underlying parameterization effort, the battery cell under study, and whether a proof of concept with conditions close to real-world applications has been performed. The advantages and disadvantages of the analyzed methods are critically discussed and evaluated with regard to their cost–benefit ratio. Finally, the finding are used to identify remaining research gaps in order to enable a transfer to electric vehicle applications.
Despite the Paris Climate Agreement and other international pledges to reduce anthropogenic carbon-dioxide emissions, road transportation emissions are increasing. Therefore, the European Union has introduced fines for exceeding CO2-limits beginning in 2025, forcing European truck manufacturers to replace diesel-powered vehicles with low-emission vehicles. Thus, hybrid, battery, and fuel cell electric trucks are in the race to become the dominant technology. Giving recommendations to decision makers, our approach to eco-efficiency combines the two disciplines of ecological and economical assessment. The study’s unified cradle-to-grave system boundary for both disciplines ensures a comprehensive and holistic forecast. To account for and project the vehicles’ future technological potential, the evolutionary algorithm NSGA-II optimizes their design parameters with regard to environmental and economic performance. To further include user requirements, we have supplemented these eco-efficiency objectives by a tractive force reserve. The results indicate that battery electric trucks have competitive costs compared to diesel-powered vehicles. We find that with today’s electricity mix, the environmental impact of battery powered is 313% higher than diesel. However, with increasing renewable energy the battery electric vehicles outperform the diesel (−65%). Operating the fuel cell with green hydrogen decreases environmental impact (−27%). BEV and FCEV potentially perform at the same costs as today’s diesel. Our study shows the impact of renewable energy on long-haul transportation and quantifies the associated costs. With this, we compare eco-efficient vehicle concepts suitable for future transportation.
Two of the main challenges for electric vehicle (EV) adoption include limited range and long recharge times. Ultra-fast charging can help to mitigate both of these concerns. However, for typical 400 V battery EVs, the charging rate is limited by the practical cable size required to carry the charging current. To reach ultra-high charge rates of 350 or 400 kW, 800 V battery EVs are a promising alternative. However, the design of an 800 V EV requires careful new considerations for all electrical systems. This paper reviews the current state of 800 V vehicle powertrain electrical design, and performs an analysis of benefits, challenges, and future trends regarding multiple vehicle powertrain components. Specifically, detailed benefits and challenges related to the battery, propulsion motor, inverter, auxiliary power unit, and on- and off-board chargers are discussed.
This study provides a comparative analysis of dynamics and hazards associated with cascading failure in lithium ion cell arrays of different cathode chemistries. Each array consists of 3×4 cylindrical cells with lithium cobalt oxide (LCO), lithium nickel manganese cobalt oxide (NMC), or lithium iron phosphate (LFP) cathode. Each array is mounted in a wind tunnel supplied with a controlled gas flow. Thermal runaway is induced in one cell using an electric heater and then observed to propagate through the array. Experiments are conducted in nitrogen and air environments to study the combustion impact. Time-resolved recordings of cells’ bottom surface temperatures are utilized to track the thermal runaway propagation and calculate a row-to-row propagation speed. The LFP cells are the only cells that do not always fully propagate thermal runaway. The speed of the propagation is found to be greater in air than in nitrogen. In nitrogen, all cells produce large amounts of hydrocarbons, CO and CO2, and minor amounts of O2 and H2. Total heats generated due to chemical reactions between cell components and flaming combustion of ejected materials normalized by the electrical energy stored are determined to be 3.5, 2.9, and 2.5 for LCO, NMC, and LFP cells, respectively.
In this paper, the energetic benefits of a multispeed transmission compared to a single speed transmission is analyzed for a long-haul truck. The truck is simulated using a reference long-haul cycle from the Vehicle Energy consumption Calculation Tool (VECTO). A nested optimization routine is used to optimize the battery, electric machine size
and the gear ratio value(s) in an outer loop with the particle swarm optimization algorithm and in the inner loop the gear shifting is optimized, as a local minimization problem. It is
found that the electric machine size can be reduced (-16%) without compromising the vehicles top speed and acceleration performance, and with a moderate reduction in energy usage (- 1.4%). The total number of gears did not significantly influence the energy usage on the long-haul drive cycle studied. The results show the potential of reducing the size of an electric machine and increase in gradeability of the vehicle with the usage of a multi-speed for trucks. Much larger gains in energy usage, without compromising performance, are expected on more dynamic driving conditions and using a dedicated (more compact and integrated) electric machine design for a multispeed transmission, which is seen as future work.
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