重庆铁马工业集团有限公司, 重庆 400050
*邮箱: heqiangcqdx@163.com
收稿:2022-11-19,
网络出版:2023-09-25,
纸质出版:2023-09-20
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何强, 刘后刚, 邹波, 等. 智能无人车辆混合储能系统选配与参数优化[J]. 兵工学报, 2023,44(9):2791-2801.
Qiang HE, Hougang LIU, Bo ZOU, et al. Selection and Parameter Optimization of Hybrid Energy Storage System for Intelligent Unmanned Vehicles[J]. Acta Armamentarii, 2023, 44(9): 2791-2801.
何强, 刘后刚, 邹波, 等. 智能无人车辆混合储能系统选配与参数优化[J]. 兵工学报, 2023,44(9):2791-2801. DOI: 10.12382/bgxb.2022.1074.
Qiang HE, Hougang LIU, Bo ZOU, et al. Selection and Parameter Optimization of Hybrid Energy Storage System for Intelligent Unmanned Vehicles[J]. Acta Armamentarii, 2023, 44(9): 2791-2801. DOI: 10.12382/bgxb.2022.1074.
面对迅猛发展的智能无人车辆及其多任务载荷用电和复杂行驶工况的大功率充放电性能要求
需要新型的储能系统方案来解决现有单一类型储能系统难以适应的问题。基于无人车辆动力性、静音里程等功率与能量性能约束
提出一种以轻量化为目标的混合储能系统(HESS)参数匹配优化方法
以实现储能系统输入输出能力与系统质量的平衡。根据无人车辆对储能系统的基本要求与不同拓扑结构特点
选配最优构型方案;基于车辆性能指标要求进行储能系统匹配计算
优化系统参数
以充分发挥HESS优势。研究结果表明:HESS能够有效减小动力电池大电流的冲击
延长电池使用寿命;新的优化方法可以有效降低能源系统的质量
提升车辆综合性能。
The rapid development of intelligent unmanned vehicles and their power demands for multi-task loads
along with high-power charging and discharging requirements under complex driving conditions
call for new energy storage system schemes that address the shortcomings of existing single-type energy storage systems. Based on the performance constraints of intelligent unmanned vehicle
such as power performance and silent mileage
a parameter matching optimization method for hybrid energy storage system (HESS) with a focus on lightweight design is proposed to achieve a balance between the input and output capacity of the energy storage system and the overall system quality. By analyzing the basic requirements of unmanned vehicles for energy storage system and the characteristics of different topological structures
the optimal configuration is selected. Based on the requirements of vehicle performance indicators
the energy storage system matching calculation is carried out
and the system parameters are optimized to give full play to the advantages of the hybrid system. The results show that HESS can effectively reduce the high current impact of the power battery and prolong its service life. Meanwhile
the optimization method can effectively reduce the weight of the energy system and improve the comprehensive performance of the vehicle.
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