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Combined optimal sizing and energy management of hybrid electric vehicles

机译:混合动力电动车的最优施胶和能量管理

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This paper describes a new methodology for sizing energy sources in hybrid electric vehicles, that enables obtaining the minimal sizing required for a given driving cycle, independently of the chosen energy management strategy. The methodology is based on two combined optimization loops: one for sizing the energy sources, using a genetic algorithm, and another one for computing the optimal energy management strategy for a specific driving cycle, using dynamic programming. Results show that the algorithm can find the best sizing of sources for the best fuel consumption, with a 6.5kW fuel cell and a 75Wh battery for the ECE driving cycle and a 9.0kW fuel cell and a 72Wh battery for the LA92 cycle. Compared to results obtained through the mean sizing power method, the algorithm shows that the hydrogen consumption can be reduced by up to 70% and the size of the battery by up to 67 %. The proposed methodology can thus help optimize the sizing of hybrid vehicles used for given driving cycles.
机译:本文介绍了一种用于混合动力电动车辆中的能源的新方法,其能够独立于所选择的能量管理策略获得给定驾驶循环所需的最小尺寸。该方法基于两个组合优化环:一个用于使用遗传算法调整能量源的一个,以及用于使用动态编程计算特定驾驶循环的最佳能量管理策略的另一个。结果表明,该算法可以找到最佳燃料消耗的最佳尺寸,具有6.5kW的燃料电池和用于ECE驱动循环的75WH电池,为LA92循环提供9.0kW燃料电池和72WH电池。与通过平均尺寸功率方法获得的结果相比,该算法表明,氢消耗可降低高达70%,电池尺寸可达67%。因此,所提出的方法可以帮助优化用于给定驾驶循环的混合动力车辆的尺寸。

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