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以单位里程成本最小化为目标的燃料电池混合动力重型牵引车最优容量配置
Optimal sizing of fuel cell hybrid electric Heavy-Duty tractor with minimum of unit mileage cost
| 作者 | Xiaoyu Wang · Shouwen Yao · Pengyu Li · Yuyang Chen · Qinghua Hao · Siqi Huang · Yinghua Zhao |
| 期刊 | Energy Conversion and Management |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 330 卷 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | An objective function minimum of unit mileage cost is put forward to attain a good balance among competing objectives. |
语言:
中文摘要
摘要 本文提出了一种针对由燃料电池系统(FCS)、电池(B)和超级电容器(SC)组成的混合储能系统(HESS)的燃料电池混合动力重型牵引车(FCHHT)的最优混合能源容量配置方法。为此,提出了一种以单位里程(10^4 km)成本(UMC)为目标函数的评价指标,用于综合评估系统的初始成本、退化成本以及氢气消耗成本。此外,提出了一种基于平均功率与荷电状态(APS)的能量管理系统(EMS),其中给出了FCS与HESS之间的功率分配策略,并通过驱动循环功率需求的平均功率、FCS最高效率点功率、FCS最大输出功率以及HESS的SOC对FCS的输出功率进行平滑处理。最后,为求解混合能源源优化问题,提出了一种癌细胞竞争与转移算法(C3MA),该算法采用高效的种群位置更新策略来模拟癌细胞的竞争与转移行为,从而更有效地探索搜索空间。C3MA通过六个基准函数进行了测试,验证了其在高维问题中的鲁棒性和快速收敛能力。对一辆49吨级牵引车进行了容量优化设计。结果表明,采用APS EMS结合C3MA、粒子群优化(PSO)和灰狼优化(GWO)算法均能稳定获得最优解。与离散小波变换(DWT)EMS相比,APS EMS使UMC降低了16%,寿命延长了77%。相较于FCS + B结构,FCS + B + SC构型使UMC平均降低了19%。
English Abstract
Abstract This paper proposes an optimal hybrid energy sources sizing methodology for fuel cell hybrid heavy-duty tractors (FCHHT) comprising fuel cell system (FCS) with battery (B) and supercapacitor (SC) as hybrid energy storage system (HESS). For this purpose, an objective function of unit mileage (10 4 km) cost (UMC) is put forward to evaluate the system’s initial cost, degradation cost, and hydrogen consumption cost. Furthermore, an average power and state of charge (APS) based Energy Management System (EMS) is proposed, where power-split strategy of FCS and HESS is given, and the output power of FCS is smoothed by the average power of drive cycle power demand, the power of maximum efficiency point and maximum power of FCS, and SOC of HESS. Finally, to solve the hybrid energy source optimization problem, the cancer cell competition and metastasis algorithm (C3MA) is proposed, where an efficient population position updating strategy is used to simulate the competition and metastasis of cancer cells, and the search space can be explored more effectively. C3MA is evaluated using six benchmark functions, demonstrating its robustness and rapid convergence in high-dimensional problems. The size optimization of a 49-ton tractor was conducted. The optimum can always be achieved using APS EMS in conjunction with C3MA, Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO). In comparison to discrete wavelet transform (DWT) EMS, APS demonstrated a 16 % reduction in UMC and a 77 % increase in lifespan. Compared to FCS + B configuration, FCS + B + SC reduces UMC by an average of 19 %.
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SunView 深度解读
该燃料电池混合动力重卡优化技术对阳光电源储能及充电业务具有重要借鉴价值。论文提出的电池+超级电容混合储能系统(HESS)架构与阳光电源ST系列PCS的多源协调控制理念高度契合,其基于平均功率和SOC的能量管理策略可应用于PowerTitan储能系统的功率分配优化。单位里程成本(UMC)优化方法为储能系统全生命周期成本评估提供新思路,特别是退化成本量化模型可增强iSolarCloud平台的预测性维护能力。C3MA优化算法在高维问题的快速收敛特性,可用于提升充电站多端口功率调度效率,支撑阳光电源在重型电动车充电领域的技术创新。