Clement Depature

Efficiency Map of the Traction System of an Electric Vehicle from an On-Road Test Drive

In this paper, the traction system modeling of a commercial electric car is studied. Experimental data acquired during an on-road test drive are used to determine an efficiency map of the traction system. Using the deduced model, simulation results are compared to experimental results. The simulation tool using the proposed efficiency map method yields less than 5 % error on energy consumption compared to experimental test drive results.

Simulation model of a multi-stack fuel cell system

The paper presents a control design oriented simulation model of a multi-stack Fuel Cell System (FCS). The aim of such a system is to improve performance, reliability and system integration versus a common single stack FCS. This paper is based on Energetic Macroscopic Representation principles and on preliminary works on FCS modeling and simulation. This paper shows the development of a complete multi-stack system simulation model from elementary parts. The used stack model is experimentally validated and simulation results of the multi-stack system are provided.

Comparison of Backstepping Control and Inversion-Based Control of a Range Extender Electric Vehicle

In this paper the drive control of a commercial Electric Vehicle (EV) equipped with a low power Range Extender (RE) Fuel Cell (FC) system is studied. By using backstepping control, the drive control of the RE-EV is deduced and compared to the Inversion Based-Control deduced from its Energetic Macroscopic Representation. From the modelling, the backstepping defines the control structure and ensures the stability of a system regarding to Lyapunov-LaSalle theorems.

Range-Extender Electric Vehicle Using a Fuel Cell

In this paper the driving range of a commercial Electric Vehicle is extended using a low power fuel cell system. By using two driving cycles (Urban Driving Cycle (UDC) and a real cycle), both vehicles are compared in simulation using Energetic Macroscopic Representation. By adding a 1.2 kW fuel cell system and 2700 sl, 19.5 kg hydrogen tanks, the driving range is extended from 105.6 km to 128.2 km for an UDC, and from 68.3 km to 73.2 km for a real cycle.

Teaching electric vehicle drive control using Energetic Macroscopic Representation

The study of an electric vehicle is an attractive topic for students. At the University of Lille1 (France), an electric car is used to teach and develop drive control skills. From software simulation and Hardware-in-the-loop simulation, the students in electrical engineering learn drive control steps with a real electric vehicle. In this paper, the Energetic Macroscopic Representation is used to describe the electric car. This graphical tool allows the decomposition of the studied vehicle in accordance with physical laws. The control scheme is then deduced from the description using the inversion-based control rules.

Impact of Heating System on the Range of an Electric Vehicle

For an accurate evaluation of the driving range of an electric vehicle (EV), many conditions must be considered (road profile, traffic influence, etc.). However, a cabin heating system is not often considered despite its significant impact. In this paper, the impact of the cabin heating system is studied on the driving range of an EV. A real EV is used as a reference. A multidomain model is developed and validated by experimental results on the vehicle. From this validated model, the impact of the heating system on the range is evaluated up to 30% in cold climatic conditions. In a classical approach, an ecodriving mode enables an increase in the range by reducing the vehicle acceleration and velocity. When considering the heating system, the energy balance is more complex: the eco-driving mode can lead to an over-consumption of energy. A better compromise is required as a function of the climatic condition.

Backstepping Control of a Fuel Cell/Supercapacitor System for Electric Vehicle

The development of the control of a Fuel Cell/Supercapacitor system for Electric Vehicle must take into account the stability constraints related to the associations of its components. Numerous studies have achieved control and energy management of Fuel Cell/Supercapacitor Electric Vehicle but real-time applications are insufficient or the stability is not ensured. In this paper, the development of a stable control of the Fuel Cell/Supercapacitor system is proposed by the backstepping method. The backstepping control design procedure is depending on different power paths and a physical decomposition prepares its design. Energetic Macroscopic Representation is used for this purpose. The vehicle power distribution is performed in simulation by the developed stable control and a proposed thermostat strategy.

Full-Scale Power Hardware-In-the-Loop Simulation of an Electric Vehicle Using Energetic Macroscopic Representation

In the automotive sector, Hardware-In-the-Loop (HIL) simulation is a useful step to develop new controls and energy management methods. We propose to develop a comprehensive and efficient full- scale power HIL simulation of a commercial electric vehicle using the graphical formalism of the Energetic Macroscopic Representation. This platform allows taking into account the limitations and component constraints at real power scale. After a validation step, we propose to modify the vehicle energy management to demonstrate the flexibility of the approach. Vehicle modifications may be validated in real time at the full-scale power.