Despite their low environmental impact, electrical vehicles have low penetration in the automotive market. Consumers are reluctant for technical reasons (limited driving range and long charging time) but also for an economic reason (high investment costs). Electric vehicle total cost of ownership (TCO) is often perceived as higher than for a thermal car, especially in Europe where diesel cars have a lower TCO than gasoline cars. Accurate TCO estimations are critical, but most of the techno-economic studies of electrified vehicles are based on very simplified energy models. In this paper, a techno-economic model is developed using an accurate technical model of an electric vehicle and a diesel car of the same segment. These technical models are validated by experimental measurements on real cars using real driving cycles. These models are then coupled to economic models to calculate TCO for a French case study. The total cost of ownership of the studied electric car is lower than for the equivalent diesel car by about 1000€ for a 5-year ownership period. Of particular importance is the finding that using real driving cycles instead of standard driving cycles decreases the TCO of electric cars while simultaneously increasing the TCO of diesel vehicles. This has implications for techno-economic models, suggesting that the typical TCO approach that uses manufacturer-reported standard cycle data may be systemically biased towards thermal vehicles. In order to understand how TCO may change in different locations, a sensitivity analysis varies different technical and economic factors. Government subsidy, ownership duration, and vehicle depreciation are the most important factors for the TCO of electric vehicles. However, TCO of the electric cars can be lower than the TCO of equivalent diesel cars under a wide range of reasonable inputs.
As stricter regulations on air quality are imposed on automotive manufacturers, simulation is playing a more important role in the electric vehicles design and production. Virtual testing helps reduce the costs of assessing vehicle performances and flaws which can be corrected early on, before the real testing is begun. This paper presents the validation, using Simcenter Amesim, of a virtual battery electric vehicle model with real measured data from the real Renault Zoe vehicle on track. The validated models give confidence in future reuse for other virtual testing scenarios, allowing to perform the tests in the digital domain, early in the development cycle, without the need of expensive and time-consuming real testing platforms.
The energy consumption of an electric vehicle is primarily due to the traction subsystem and the comfort subsystem. For a regular trip, the traction energy can be relatively constant but the comfort energy has variation depending on seasonal temperatures. In order to plan the annual charging operation of an eco-campus, a simulation tool is developed for an accurate determination of the consumption of an electric vehicle throughout year. The developed model has been validated by comparison with experimental measurement of a real vehicle on a real driving cycle. Different commuting trips are analyzed over a complete year. For the considered city in France (Lille), the comfort energy consumption has an overconsumption up to 33% in winter due to heating, and only 15% in summer due to air conditioning. The urban commuting driving cycle is more affected by the comfort subsystem than extra-urban trips.
The reduction of greenhouse gas emission is necessary to limit the global warming. Electrification of the transport sector is one solution. To accelerate the change, accurate and fast simulation program are one of the key issues. The choice of the accurate model is an important aspect to the simulation program. In this paper, different models of an electric drive for an electric vehicle are compared in terms of computation time and energy consumption. A static model will lead to divide the computation time by 100, by losing only 2% of accuracy
The PANDA project is a Research Innovation Action from the European H2020 programme. PANDA will enable the automotive industry to speed up design and testing of innovative electrified vehicles. In the PANDA project, multi-scale and multi-domain simulation packages are developed to interconnect all components of electrified vehicles. The EMR (Energetic Macroscopic Representation) formalism is used to unify the model organization. Moreover, all the models will be shared in a cloud for both stand-alone simulation and cloud computing. On the contrary to existing solutions which are based on a structural philosophy, PANDA is focused on functional-based approach. First results are provided to compare both approaches for the simulation of an electric vehicle. The EMR-based functional library leads to a reduced computation time of 15% in comparison with a structural-based simulation. This results confirms the ability of the PANDA solution for real-time simulation in particular for Hardware-In-the-Loop testing.