Research on energy management and control for six-wheel-drive electric bus rapid transit with photovoltaic-battery-supercapacitor

被引:1
|
作者
Yang, Kun [1 ]
Wang, Zhongwei [1 ]
Shao, Changjiang [2 ]
Ma, Chao [1 ]
Tan, Di [1 ]
Wang, Wei [3 ]
机构
[1] Shandong Univ Technol, Sch Transportat & Vehicle Engn, Zibo 255000, Peoples R China
[2] Weichai Power Co Ltd, WeiFang, Peoples R China
[3] CATARC Automot Test Ctr Tianjin Co Ltd, Tianjin 300300, Peoples R China
关键词
Hybrid energy storage system; Life cycle cost function; Optimal supercapacitors size; Dynamic programming algorithm; Coordinated control; Comprehensive energy efficiency; MODEL-PREDICTIVE CONTROL; TIME POWER MANAGEMENT; DISTRIBUTION STRATEGY; STORAGE SYSTEM; VEHICLES; TORQUE;
D O I
10.1016/j.est.2023.109828
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Electric Bus Rapid Transit is an effective solution to traffic congestion and environmental pollution. At present, Electric Bus Rapid Transit needs to be equipped with a large number of power batteries, which brings the key problems of long charging time, short driving range, and high comprehensive utilization cost. To solve the above problems, a novel six in-wheel motors driving Electric Bus Rapid Transit scheme with photovoltaic cells, lithiumion batteries and supercapacitors (SWEBRT-PBS) is studied, constrained by the cost and comprehensive energy efficiency of vehicle. First, the system architecture for hybrid energy storage system composed of photovoltaic cells, lithium-ion batteries and supercapacitors (PBS) is analyzed. The life cycle cost function for PBS based on the degradation cost of lithium-ion batteries and the electricity cost of each energy source is proposed. The dynamic programming algorithm is employed to optimize the life cycle cost function of PBS, and then to obtain the optimal size of matches for supercapacitors. Second, the fixed step disturbance observation method is adopted to ensure stable power output in the maximum power point tracking controller of photovoltaic cells based on the vehicle application environment. Third, the power control rules are extracted based on the optimization results of dynamic programming algorithm, and the power allocation strategy for PBS with dynamic programming algorithm joint rules is formulated. Fourth, the overall efficiency function for driving system is established and optimized based on the sequential quadratic programming algorithm. The collaborative optimization strategy for SWEBRT-PBS is developed based on the corresponding optimization results, PBS operating modes and vehicle operating modes. The results show that the SWEBRT-PBS can reduce the number of lithiumion batteries, thereby reducing the vehicle mass by 1.27 % and increasing the vehicle space utilization by 1.81 %. In addition, the comprehensive energy efficiency of vehicle can be improved by 28.79 %.
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页数:23
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