Energy Management Strategy for the Hybrid Energy Storage System of Pure Electric Vehicle Considering Traffic Information

Abstract

The main challenge for the pure electric vehicles (PEVs) with a hybrid energy storage system (HESS), consisting of a battery pack and an ultra-capacitor pack, is to develop a real-time controller that can achieve a significant adaptability to the real road. In this paper, a comprehensive controller considering the traffic information is proposed, which is composed of an adaptive rule-based controller (main controller) and a fuzzy logic controller (auxiliary controller). Through analyzing the dynamic programming (DP) based power allocation of HESS, a general law for the power allocation of HESS is acquired and an adaptive rule-based controller is established. Then, to further enhance the real-time performance of the adaptive rule-based controller, traffic information, which consists of the traffic condition and road grade, is considered, and a novel method combining a K-means clustering algorithm and traffic condition is proposed to predict the future trend of vehicle speed. On the basis of the obtained traffic information, a fuzzy logic controller is constructed to provide the correction for the power allocation in the adaptive rule-based controller. Ultimately, the comparative simulations among the traditional rule-based controller, the adaptive rule-based controller, and the comprehensive controller are conducted, and the results indicate that the proposed adaptive rule-based controller reduces battery life loss by 3.76% and the state of change (SOC) consumption by 3.55% in comparison with the traditional rule-based controller. Furthermore, the comprehensive controller possesses the most excellent performance and reduces the battery life loss by 2.98% and the SOC consumption of the battery by 1.88%, when compared to the adaptive rule-based controller.