Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules

Zhengkai Wu, Jiazhong Wang (), Yazhou Xing, Shanshan Li, Jinggang Yi and Chunming Zhao
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Zhengkai Wu: College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
Jiazhong Wang: College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
Yazhou Xing: College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
Shanshan Li: College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
Jinggang Yi: College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
Chunming Zhao: Tianjin Yidingfeng Power Technology Co., Ltd., Tianjin 300380, China

Agriculture, 2023, vol. 13, issue 7, 1-18

Abstract: In order to ensure the continuity and endurance mileage requirements during sowing operations, it is necessary to establish accurate modeling for the working condition of the electric tractor sowing unit by adopting a reasonable energy management strategy and realizing accurate energy prediction. The existing electric tractor sowing unit battery energy management strategy is not optimal since it is mostly based on extensive rules. In this paper, according to the requirements of the sowing conditions, a precise model of electric energy consumption in the sowing cycle was established and an energy management strategy of sowing unit of extended-range electric tractor with power CD-CS was proposed. Fuzzy control rules of the dynamic SOC correction factor were established in the battery maintenance stage, and the NSGA-II algorithm was used to optimize the fuzzy control rules to optimize the battery charging and discharging efficiency. A hardware-in-the-loop simulation test platform was built, and the proposed CD-CS strategy was compared with the fuzzy improvement strategy. The simulation results show that the proposed fuzzy improvement strategy extended the battery life of the power consumption stage by 2131.9 s, which is a significant improvement. The field practical results showed that the SOC decreased by 7.21% and the simulation by 4.94% in terms of power consumption in a cycle. The power consumption variance was within a reasonable range, which further verifies the feasibility of the strategy.

Keywords: extended-range driverless electric tractor; seeding set; energy management; CD-CS; fuzzy control (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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