A Predictive and Battery Protective Control Strategy for Series HEV

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 as replacement costs is a deterring factor for consumers. This paper proposes an improved power follower control strategy for series hybrid electric vehicles based on protection of the vehicle's battery and prediction of the future vehicles' path. First, a fuzzy predictive algorithm is integrated into a conventional power follower management system such that the future path information of the vehicle is taken into account for generation of the control signals. Then, the energy management system is augmented with a new tool to increase the state of the health (SOH) of the power train battery. Furthermore, since Valve Regulated Lead Acid (VRLA) batteries are of great importance in HEV technology, a new method based is used to optimize the charging current for these batteries, in order to decrease charging time and improve battery lifetime. 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.