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Issue title: Special Section: Intelligent Algorithms for Complex Information Services - Recent Advances and Future Trends
Guest editors: Andino Maseleno, Xiaohui Yuan and Valentina E. Balas
Article type: Research Article
Authors: Qi, Wanqiang; *
Affiliations: College of Automotive Engineering, Jilin Engineering Normal University, Changchun, Jilin, China
Correspondence: [*] Corresponding author. Wanqiang Qi, College of Automotive Engineering, Jilin Engineering Normal University, Changchun 130052 Jilin, China. E-mail: [email protected].
Abstract: The main reason that currently hinders the commercialization of electric vehicles is a bottleneck in battery, motor and electronic control technology, however, an In-depth study of electronic control technology is one of the most effective means to break through this bottleneck at present. The purpose of this paper is to solve the problem that the pure electric vehicle is difficult to meet the driver’s acceleration intention in the urban road cycle acceleration work condition and the brake energy recovery process does not consider the battery state of charge during the deceleration work condition. Proposed a control strategy that can meet the requirements of road cycle conditions and driver’s driving intentions and take account of the vehicle operating status. Use a fuzzy control algorithm to develop a fuzzy controller that taking the motor demand speed change rate and battery state of charge as input, the motor demand torque compensation coefficient as output. The experimental results show that the modified control strategy can improve the actual output power, the actual output torque of the motor and actual driving force of the wheel under the premise of maintaining economy; it also improved the acceleration performance and climbing performance of pure electric vehicles, and can recycle braking energy efficiently. The experimental results show that the secondary development control strategy can meet the requirements of the cycle work condition CYC_ECE_EUDC for the speed and driving force and the driver’s driving intention under the premise of not sacrificing economics.
Keywords: Pure electric vehicle, driving intention, fuzzy control strategy, driver PID model
DOI: 10.3233/JIFS-179998
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5131-5139, 2020
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