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Finding optimal driving strategy of electric vehicle during deceleration with serial regenerative braking

机译:串联再生制动在电动汽车减速过程中的最佳驱动策略

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One of the primary advantages of electric vehicle (EV) is to easily incorporate a regenerative braking system where the lost KE during braking is restored into the vehicle energy storage. But, due to limited energy storage, inadequate charging station and long charging time, the braking energy regeneration is required to be maximized to enhance the EV range. Since driving harshness has a great influence on the regeneration efficiency, an optimal driving strategy during deceleration of an EV is determined here by solving a multi-objective optimization problem (MOOP). The MOOP is solved based on three primary conflicting objectives, namely minimization of deceleration duration, maximization of regenerative braking energy and minimization of jerk. Optimization results are presented for a representative speed change in different driving cycles. After analysing the Pareto-fronts, a zone of optimal driving is identified. During deceleration, driver selects a solution (driving strategy) from the zone based on higher level information such as safe distance to avoid accident, etc.
机译:电动汽车(EV)的主要优势之一是可以轻松地将再生制动系统纳入其中,从而将制动过程中丢失的KE恢复到车辆的能量存储中。但是,由于有限的能量存储,不足的充电站和较长的充电时间,需要最大化制动能量再生以增加EV范围。由于行驶苛刻度对再生效率有很大影响,因此在这里通过解决多目标优化问题(MOOP)来确定EV减速期间的最佳行驶策略。 MOOP的解决基于三个主要的冲突目标,即最小化减速持续时间,最大化再生制动能量和最小化急动度。给出了针对不同驾驶循环中的典型速度变化的优化结果。在分析了帕累托前线之后,确定了最佳驾驶区域。减速期间,驾驶员会根据安全距离等更高级别的信息从区域中选择解决方案(驾驶策略),以避免发生事故等。

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