In order to democratize electric vehicles, automakers have to give a solution to reduce the Total Cost of Ownership (TCO) and bring it better than thermal vehicles one. This paper presents results of works on costs improvement of a 3.5t light-duty commercial electric vehicle. TCO (Total Cost of Ownership) was separated into investment costs and operating costs. The batteries of an electric vehicle were the most expensive element of the powertrain, which can represent until 45% of the vehicle price. What's more, contrary to the life of thermal vehicles, electric energy storage systems have a limited life around 5 years, highly dependent on conditions of use. Thus, study of batteries represents a capital step toward TCO improvement. Inspired by literature, battery aging model is proposed and identified by the calendar and cycling aging tests. A multi-physical model of the battery, including aging, was identified and incorporated inside the energetic vehicle model. Charging strategies were developed and adapted to operate according to the influence of the conditions of use. These models and strategies are integrated in a software tool. Taking into account the intended use of the vehicle, this tool, first, designates the most suitable battery solution dimensions, and then, associates the charging strategy to the requirements of use, in order to ensure the best battery life or the lowest TCO.

This study presents a design methodology applied to design and improve the efficiency of interleaved Buck converters. This methodology is based on a multi‐physic and multi‐objective optimisation to ensure well integration of the converters. Thereto, the number of cells is used as a key parameter to formalise this approach with analytical models established to offer compromise needed between the computation time and results accuracy. The proposed methodology is applied to an interleaved buck converter for automotive application to achieve the requirements as electrical, volume, efficiency and thermal constraints. It allows to find the optimal converter architecture by searching the minimum volume integration and maximum efficiency by depicting the optimal number of cells and adequate active and passive component technologies selected from a manufacturer database. This methodology is drawn up to remove the risk of feasibility on the converter configuration earlier during the design process considering multi‐physic constraints.

Energy Management and Control Strategy of Hybrid Energy Storage System for Fuel Cell Power Sources

Interleaved converters use an increased number of power electronics switches; this may subsequently affect their reliability. However, this is an opportunity to develop fault-tolerant strategies to improve their reliability and to ensure continuity of service. This is why we herein propose, for the first time, a mathematical function to simultaneously model the healthy and faulty conditions of each switch, thus enabling a unique model of the system. This model is then used in an original fault-tolerant strategy based upon the peak current control with slope compensation. This method not only extends the stable range of the load variation but also ensures the stability in faulty conditions. Finally, the simulation results validate its effectiveness and confirm the theoretical analysis.

Companies always search for alternative solutions for designing mechatronic systems in more efficient ways to cope with the high-performance standards, competitive market and design time reduction. This paper presents a complete multi-physical approach to design and validate an Electronic Throttle Body (ETB) system in a concurrent way. Our goal is to reduce the modeling and test efforts by using an enriched multi-physical model in the preliminary phase. This model is the main stone that connects different fields and ensures efficient collaboration. This paper is the result of a close collaboration between laboratories and industrials in the automotive field and aims at developing a methodology that takes into account collaboration constraints during design. Thanks to this approach, industrial requirements of the ETB are achieved at an early stage. An experimental test bench is presented to validate the simulation results.

With the increasing adoption of electric vehicles (EVs), optimizing lithium-ion battery capacity is critical for overall powertrain performance. Recent studies have optimized battery capacity in isolation without considering interactions with other powertrain components. Furthermore, even when the battery is considered within the full powertrain, most works have only modeled the electrical behavior without examining thermal or ageing dynamics. However, this fails to capture systemic impacts on overall performance. This study takes a holistic approach to investigate the effects of battery capacity optimization on convergence of the full EV powertrain. A battery multiphysics model was developed in MATLAB/Simulink, incorporating experimental data on electrical, thermal, and ageing dynamics and interactions with other components. The model was evaluated using real-world WLTP and Artemis driving cycles to simulate realistic conditions lacking in prior works. The findings reveal significant impacts of battery optimization on total powertrain performance unaccounted for in previous isolated studies. By adopting a system-level perspective and realistic driving cycles, this work provides enhanced understanding of interdependent trade-offs to inform integrated EV design.