Research on Acceleration Curve Optimization of Electric Vehicle based on Energy Consumption

IEEA '18 Pub Date : 2018-03-28 DOI:10.1145/3208854.3208890
Qin Liu, Lifu Li
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引用次数: 2

Abstract

Aiming at the problem that the energy consumption of electric vehicle (EV) was quite different under different acceleration curves, using a typical EV as the research object, and the difference of EV energy consumption between acceleration curves with a single acceleration value and multiple acceleration values was studied by mathematical induction. On this basis, this study established acceleration curve optimization model based on acceleration characteristic parameters, and proposed a genetic optimization method for EV acceleration curves to minimize energy consumption per kilometer. The EV acceleration curve was optimized under the constraint of minimizing energy consumption and driving comfort. The optimal acceleration curve with the lowest energy consumption per kilometer was obtained, and its acceleration characteristic parameter was. To validate the reliability of optimization result, the EV test in different acceleration curves was carried out. The results showed that, the optimized acceleration curve with multiple acceleration values was more effective in minimizing EV energy consumption per kilometer than that of a single acceleration value, and for the same duration, the optimized acceleration curve reduced energy consumption per kilometer by up to 2.23%.
基于能耗的电动汽车加速曲线优化研究
针对不同加速度曲线下电动汽车能耗差异较大的问题,以一辆典型电动汽车为研究对象,采用数学归纳法研究了单加速度曲线与多加速度曲线下电动汽车能耗差异。在此基础上,建立了基于加速度特征参数的加速曲线优化模型,提出了一种以每公里能耗最小为目标的电动汽车加速曲线遗传优化方法。在能耗和驾驶舒适性最小化的约束下,对电动汽车加速曲线进行了优化。得到了单位公里能耗最低的最优加速度曲线,其加速度特性参数为。为了验证优化结果的可靠性,进行了不同加速曲线下的EV试验。结果表明,与单一加速度值相比,多加速度值优化后的加速曲线能更有效地降低电动汽车的公里能耗,在相同的持续时间内,优化后的加速曲线可使电动汽车的公里能耗降低2.23%。
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