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An adaptive power distribution control strategy for an electric vehicle with dual-motor coupling in consideration of road gradient

机译:考虑道路梯度双电机耦合电动车辆的自适应配电控制策略

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摘要

An optimal power distribution control strategy is proposed in consideration of road gradient. Two original contributions are made to distinguish our work from current research. First, a sub-optimal State of Charge (SOC) predictive model is proposed based on Back Propagation (BP) neural network. The sampling set of the BP is obtained from the optimal results from Dynamic Programming (DP), based on a series of driving cycles in real-world and the corresponding road gradient. Second, an adaptive control method based on PID is proposed with the designed sub-optimal SOC predictive model. Specifically, the optimal shift schedule of the coupler is designed offline based on DP and is implemented into the controller in a prior fashion, to decouple the relationship between the coupler and the motors. Simulation results demonstrate that the proposed adaptive control strategy can realise optimally real-time power distribution control and is better than rule-based power distribution strategy.
机译:考虑到道路梯度,提出了最佳配电控制策略。 两个原始捐款是为了区分当前研究的工作。 首先,基于反向传播(BP)神经网络提出了一种次优电荷(SOC)预测模型。 基于现实世界和相应的道路梯度的一系列驾驶循环,从动态编程(DP)的最佳结果获得了BP的采样集。 其次,利用设计的次优SOC预测模型提出了一种基于PID的自适应控制方法。 具体地,耦合器的最佳移位计划基于DP的离线设计,并且以先前的方式实现到控制器中,以将耦合器和电动机之间的关系分离。 仿真结果表明,所提出的自适应控制策略可以实现最佳的实时配电控制,并且优于基于规则的功率分布策略。

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