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Mathematical Problems in Engineering
Volume 2016, Article ID 6185743, 13 pages
http://dx.doi.org/10.1155/2016/6185743
Research Article

Design and Optimization of the Power Management Strategy of an Electric Drive Tracked Vehicle

College of Field Engineering, PLA University of Science and Technology, Nanjing 210007, China

Received 2 April 2016; Revised 8 August 2016; Accepted 16 August 2016

Academic Editor: Yan-Jun Liu

Copyright © 2016 Qunzhang Tu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This article studies the power management control strategy of electric drive system and, in particular, improves the fuel economy for electric drive tracked vehicles. Combined with theoretical analysis and experimental data, real-time control oriented models of electric drive system are established. Taking into account the workloads of engine and the SOC (state of charge) of battery, a fuzzy logic based power management control strategy is proposed. In order to achieve a further improvement in fuel economic, a DEHPSO algorithm (differential evolution based hybrid particle swarm optimization) is adopted to optimize the membership functions of fuzzy controller. Finally, to verify the validity of control strategy, a HILS (hardware-in-the-loop simulation) platform is built based on dSPACE and related experiments are carried out. The results indicate that the proposed strategy obtained good effects on power management, which achieves high working efficiency and power output capacity. Optimized by DEHPSO algorithm, fuel consumption of the system is decreased by 4.88% and the fuel economy is obviously improved, which will offer an effective way to improve integrated performance of electric drive tracked vehicles.