A Fuzzy Energy Management Strategy for Series Hybrid Electric Vehicle with Predictive Control and Durability Extension of the Battery

Abstract

Hybrid electric vehicles (HEV) are superior to conventional vehicles from the standpoint of environmental issues. Many factors involve in designing HEVs such as fuel consumption, emission and performance. A major challenge for development of hybrid vehicles is coordination of multiple energy sources and converters, and in case of a HEV, power flow control for both mechanical and electrical path. This necessitates the utilization of appropriate control or energy management strategy. Furthermore, the durability extension of some critical components in the drive train such as batteries tends to be one of the substantial factors considered in designing control strategies for HEVs. In this paper two novel issues are considered in designing energy management systems for series HEVs. In the first part, we propose an algorithm such that the future path information of the vehicles is also taken into account for generating the control signals. Using global positioning system (GPS) installed today in most of the vehicles, such data are fed to the central vehicle controller. A fuzzy logic controller (FLC) is utilized for energy management based on the predicted future state of the vehicle, in order to improve fuel consumption, emission and performance. Then, the energy management system is modified to increase the state of the health (SOH) of the power train battery. This approach, which results in the extension of the battery life, is called predictive and protective algorithm (PPA). The simulation results verify the effectiveness of the proposed controllers.