Ali Castaings

Different Control Schemes of a Battery/Supercapacitor System in Electric Vehicle

This paper deals with energy management for electric vehicle using SuperCapacitors (SCs) and battery. SCs are connected to the DC bus through a converter whereas battery is directly connected to the DC bus. Using the inversion-based rules of Energetic Macroscopic Representation (EMR), a systematic control structure can be deduced. Some differences can be shown in comparison with classical control schemes. This paper aims to compare a control scheme deduced from EMR and another control structure designed thanks to a more classical way. It can be noticed that some differences appear. As far as the structure is concerned, the number of sensor can be reduced in the EMR case. In terms of performances, some control errors appear in the classical scheme case.

Adaptive Optimisation-Based Strategy of a Battery/Supercapacitor System for EV

Optimisation-based Energy Management Strategies for hybrid and electric vehicles have to face some issues for real-time applications. In this study,an online adaptive optimisation-based strategy is used for an electric vehicle with a Hybrid Energy Storage System including supercapacitors and batteries. The SCs voltage limitations are taken into account by using a feedback control. Indeed the voltage limitation is a key point for safe operations in the vehicle. A comparison with a more classical optimisation-based method is performed by simulations on a normalised driving cycle. The results point out a more effective behaviour of the adaptive strategy.

Energy management in EVs using battery and supercapacitors: Algebraic loop issue

This paper deals with inversion-based control of EVs with Hybrid Energy Storage System based on battery and supercapacitors. Using inversion rules of Energetic Macroscopic Representation (EMR), a systematic control structure can be deduced. However, it points out the possibility of an algebraic loop issue. Furthermore, it may result in computation problems. This paper aims to exhibit some solutions to avoid this problem in an efficient way.

Decomposed Energy Management of a Multi-Source Fuel Cell Vehicle Using Energetic Macroscopic Representation

Energy management of multi-sources vehicles is a complex task. The higher the number of sources becomes, the higher the complexity is. In this study, a decomposed energy management strategy is used for a vehicle fed by three energy sources: a fuel-cell, a battery and supercapacitors. This decomposition allows simplifying the synthesis of the Energy Management Strategy. A comparison with a fuel cell vehicle is performed by simulation. By imposing a constant current to the fuel-cell, the developed strategy enables to improve the fuel cell lifetime. Moreover, the fuel consumption is reduced in comparison with the pure fuel-cell vehicle.