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• W3042777650 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." @default.
• W3042777650 created "2020-07-23" @default.
• W3042777650 creator A5039448167 @default.
• W3042777650 date "2020-10-21" @default.
• W3042777650 modified "2023-10-18" @default.
• W3042777650 title "Fuzzy control strategy of pure electric vehicle based on driving intention recognition" @default.
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• W3042777650 doi "https://doi.org/10.3233/jifs-179998" @default.
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