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首页> 外文期刊>International journal of computing science and mathematics >A genetic-fuzzy control method for regenerative braking in electric vehicle
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A genetic-fuzzy control method for regenerative braking in electric vehicle

机译:电动汽车再生制动的遗传模糊控制方法

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In order to improve the recovery ratio of the regenerative braking energy in electric vehicles, the influence factors on braking energy feedback in electric vehicles were analysed. Then, a parallel braking force distribution model was established, and a fuzzy controller on braking force distribution was designed, in which the inputs were vehicle speed, braking strength, battery SOC, and output was regenerative braking ratio. On the other hand, the implementation of genetic algorithm in optimisation process was studied. Furthermore, the genetic algorithm was used to optimise the fuzzy control rules, and new fuzzy distribution rules of electro-hydraulic braking force were obtained. The experimental results showed that the recoverable energy ratio was increased by 2.7% with the comparison of the optimised distribution rules and the original rules. So, the genetic-fuzzy control method is effective for regenerative braking in electric vehicles.
机译:为了提高电动车中再生制动能量的回收率,分析了电动车辆制动能量反馈的影响因素。然后,建立了平行制动力分布模型,设计了一种对制动力分布的模糊控制器,其中输入是车速,制动强度,电池SOC,输出是再生制动比的。另一方面,研究了遗传算法在优化过程中的实现。此外,遗传算法用于优化模糊控制规则,并获得了电液制动力的新模糊分布规则。实验结果表明,随着优化的分配规则和原规则的比较,可收回的能量比增加了2.7%。因此,遗传模糊控制方法对于电动车辆中的再生制动是有效的。

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