Impact of passenger thermal comfort and electric devices temperature on range: a system simulation approach

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

Battery Management System Evaluation within a Complete Electric Vehicle Model with Software-in-the-Loop and Hardware-in-the-Loop Approaches

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

Comparison of Energetic Macroscopic Representation and structural representation on EV simulation under Simcenter Amesim

European Union (EU)Horizon 2020International audienceThe 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