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Loss Optimization and Ultracapacitor Pack Sizing for Vehicles with Battery/Ultracapacitor Hybrid Energy Storage

机译:电池/超容器混合储能的车辆损耗优化和超超容量包装

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Battery and ultracapacitor hybrid energy storage systems have long been proposed as alternatives to battery-only systems for electrified vehicles. Prior research has focused on system topologies, dc/dc converter design, control methods, and evaluating specific applications. This work utilizes a rule-based control method and dynamic programming combined with a vehicle model to evaluate the reduction in energy storage losses that can be achieved for various drive cycles and ultracapacitor pack sizes. Dynamic programming is used to determine the optimum power split between the battery and ultracapacitor pack for a specified drive cycle and calculates the best performance a causal control algorithm could achieve. The analysis shows that dynamic programming can significantly improve the loss reductions compared to the basic rule-based control, making it possible to reduce the size of the ultracapacitor pack needed to deliver meaningful energy savings. Experimental tests have been carried out on battery and ultracapacitor cells that raise confidence in the accuracy of the model predictions for drive cycle metrics.
机译:长期以来,电池和超薄电池混合能量存储系统已被提出作为仅电池电气的电池系统的替代品。现有研究专注于系统拓扑,DC / DC转换器设计,控制方法和评估特定应用。该工作利用基于规则的控制方法和动态编程与车辆模型相结合,以评估可以实现各种驱动循环和超容器包装尺寸的能量存储损耗的降低。动态编程用于确定指定的驱动周期的电池和超容器包之间的最佳功率分配,并计算最佳性能,可以实现因果控制算法。分析表明,与基于基本规则的控制相比,动态规划可以显着提高损耗减少,使得可以减小提供有意义的节能所需的超级扫描器包的尺寸。实验测试已经在电池和超级电池细胞上进行,其提高了对驱动周期度量的模型预测的准确性的置信度。

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