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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.

A detailed battery pack model has been developed within Simcenter Amesim by Siemens Industry Software. The model illustrates the Battery Management System (BMS) control development process from Model in the Loop (MiL), Software in the Loop (SiL) to Hardware in the Loop (HiL). The battery pack model has been integrated in a validated vehicle model, which corresponds to an existing vehicle developed by Voltia, named the Voltia eVan. This originally diesel engine powered light duty trucks have been electrified. The electrified version has been tested on the roller bench at the Eindhoven University of Technology. The interest of detailing the battery pack model is to have access to a multiple virtual temperature and voltage sensors, which allows validating the balancing methodologies that could be integrated in a BMS. A real-time analysis of the model has been conducted to ensure the model is compatible with the control constraint of the BMS. Finally, the complete model has been connected to a functional BMS in order to validate the approach. For that purpose, several BMS functions have been implemented in the control model developed with MATLAB/Simulink, such as the state of charge (SOC) estimation, the cell balancing, the charge/discharging and the thermal management. Once the cosimulation in SiL environment has been validated, a test on HiL platform has been done in real-time condition in order to reproduce realistic cell balancing and to study charging strategies, which are key functions to ensure better lifetime of the battery.

International audience; The automotive industry is shifting to mass production of electrified vehicles. Simulation is a key step for developing these new vehicles. System simulation tools as Simcenter Amesim includes ready-to-use multi-physics libraries in that perspective. A new library is being created based on the Energetic Macroscopic Representation formalism to speed-up the battery electric vehicles (BEV) development process. The paper presents the BEV multi-level simulation where the simulations were done using 3 different levels for the battery models. By using “plug & play” method different BEV model configurations can be built in a fast, precise and systematic way.

Battery autonomy and drive range of Electric Vehicles could be improved by smart control of the power flows requested by equipped systems. In this paper, the authors propose two energy-saving strategies, acting respectively in the electric driveline consumption minimization and in the auxiliary power allocation policy. Developed solutions aim at the reduction of the power demand, both concerning e-powertrain and sub-components, not directly related to traction purpose, enhancing corresponding driveability distance. Evaluation of the result is done through a model-based approach, using a concept e-car proposed by Valeo and implemented in a co-simulation environment, between Amesim and Simulink. The investigated methodology appears as a useful tool for the optimal design of the vehicle sub-system and component.

Energy Consumption of Auxiliary Systems on electric vehicles has an important role in reducing the overall autonomy since their contribution especially for what concern HVAC Systems is often not negligible and not correlated to vehicle kinematics. In this work authors propose a quite simple architecture to adopt an intelligent management of on board loads in order to increase the level of correlation between vehicle dynamics and applied auxiliary loads in order to smooth the overall power demand for vehicle storage system which is should be stressed by transients in which both traction and auxiliary loads are applied at the same time.

The software-in-the-loop and hardware-in-the-loop tests of a battery management system require a real-time compatible electro-thermal battery pack model. In our study, a numerically complex electrochemical-thermal model has been characterized from experimental data of a nickel-rich, silicon-graphite 18650-type lithium-ion cell. While it accurately represents the electro-thermal battery behavior, it is hardly suitable for real-time application due to its intensively numerical solving effort and related calculation time if no huge numerical efforts are applied to reduce the model. The objective of this paper is to present a simple method to derive a reduced-order electro-thermal cell model from the complex electrochemical-thermal cell model and build a real-time compatible battery pack model with the reduced-order cell model.

European Union (EU)Horizon 2020; International audience; The development of electric vehicles has been spectacular over the last 20 years, so the automotive industry has started to shift mass production of electrified vehicles. However, new electrified vehicles are required to face the needs of the users. Simulation is a key step for development of new vehicle. Organization tools, such as Energetic Macroscopic Representation (EMR), have therefore been developed to improve and speed-up the development of virtual electric vehicle models. The paper presents a comparison between functional and a structural representation on EV simulation under Simcenter Amesim. This paper studies the impact of the two representations on the simulation results and time. For this purpose, an EMR library for the Simcenter Amesim simulation tool has been developed.

In this paper, two main objectives were pursued: validate a battery model through measured data and simulate an electric vehicle using the confirmed battery model. The experimental results obtained in the test of the Renault ZOE electric car have been used. The test consisted in achieving a required speed profile, being navigated 83 km in a 6267 seconds driving cycle. We considered two battery models: quasi-static and dynamic. The electric vehicle model is powered by the validated-by-measurements battery dynamic model. Considering the speed profile as input for both simulations, battery and vehicle, the simulation results are compared with the test results. Appropriate models have been developed to ensure a good correlation with experimental results. This study represents a foundation for future researches about the development of the virtual car model using converter and more complex electric motor models.

Application of regenerative braking on electric vehicles has to be carefully optimized in order to maximize the system efficiency, maintaining high performance and reliability levels that are required by the automotive sector. Considering complex interactions arising from the interaction of electric brake plant with vehicle dynamics and other on-board sub-systems, there is the necessity of modular scalable models able to merge multiple competences and different engineering tools, aimed at performing accurate simulation activities. In this work authors present some preliminary results concerning the implementation of a model in which the potentialities of co-simulation between different environment are exploited.

The range of Electric Vehicles is highly influenced by the electric power consumed by auxiliaries, a huge part of this power being used for cabin heat-up and cool-down operations in order to ensure an acceptable level of thermal comfort for the passengers. Driving range decreases with low temperatures in particular because cabin heating system requires an important amount of electric power. Range also decreases with high ambient temperatures because of the air conditioning system with electrically-driven compressor. At the same time, batteries and electric motors operates at their maximal efficiency in a certain range of temperature. The reduced EV driving range under real life operating cycles, which can be a barrier against market penetration, is an issue for further development in the future towards sophisticated cabin heating and cooling systems, as well as battery warmer. The aim of this paper is to highlight the benefits of a system simulation approach, based on LMS Imagine.Lab AMESim, in order to estimate the impact of various technologies of cabin heating and cooling on both the cabin temperature and the driving range. In this paper, a battery electric vehicle including a cabin heating with PTC device and a R134a refrigerant loop is simulated under various ambient temperatures on a given driving cycle with the same required cabin temperature target. Simulation outputs include the cabin temperature evolution, the battery state of charge and as a consequence the driving range.

Die Entwicklung von Kuhlsystemen wird angetrieben durch die kommende Gesetzgebung zur CO2-Reduzierung. Valeo beschreibt eine innovative Kuhlsystemarchitektur, die aus zwei modularen Kuhlmittelkuhlern im Fahrzeug-Frontend besteht. Dieses neu entwickelte „Ultimate Cooling“-System ist gekennzeichnet durch miteinander verbundene Niedrig- und Hochtemperatur-Kuhlmittelkreislaufe. Zusammen mit einer angepassten Regelstrategie wird die Warmeabfuhrkapazitat der im Fahrzeug-Frontend eingebauten Kuhlmittelkuhler optimiert. Mess- und Simulationsergebnisse zeigen die Vorteile des neuen Systems in einem Demonstrationsfahrzeug mit Euro-4-Dieselmotor sowie mit hochaufgeladenem (80 kW/l) Euro-6-Dieselmotor.

Cooling system development is driven by upcoming CO2 reduction legislation. Valeo highlights an innovative cooling system architecture, which uses two modular main coolant radiators in the vehicle frontend. This newly developed “Ultimate Cooling” system has both low temperature and high temperature coolant loops, which are connected with each other. It allows together with an adapted control strategy to optimize the available heat dissipation capacity installed by the radiators in the vehicle front end. Results of measurements and simulation show the advantages of this new system in a demo-car with a Euro-4 diesel engine (50 kW/l) and a highly charged (80 kW/l) Euro-6 diesel engine.