Fuzzy Adaptive Energy Management Strategy for a Hybrid Agricultural Tractor Equipped with HMCVT

Zhen Zhu, Lingxin Zeng, Long Chen, Rong Zou and Yingfeng Cai ()
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Zhen Zhu: Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
Lingxin Zeng: Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
Long Chen: Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China
Rong Zou: School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, China
Yingfeng Cai: Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China

Agriculture, 2022, vol. 12, issue 12, 1-21

Abstract: In order to solve the problem of high fuel consumption and poor emission performance in high horsepower tractors, a parallel hybrid tractor system was designed using a dual power source of an engine and motor matched with a hydro-mechanical continuously variable transmission (HMCVT). An equivalent fuel consumption minimization strategy (ECMS) was used for power distribution of this hybrid system. To address the problem of poor adaptability of the equivalence factor to different working cycles in the conventional ECMS, a fuzzy adaptive equivalent fuel consumption minimization strategy (FA-ECMS) was proposed. A fuzzy PI controller based on battery SOC (State of Charge) feedback was designed to adjust the equivalence factor in real time, so as to achieve adaptive control of the equivalence factor. The physical model of the system was built by SimulationX, and the model of the control strategy was built using Matlab/Simulink. Two typical cycles of tractor plowing and road transportation were simulated. Under ECMS, the fuel consumption of the hybrid agricultural tractor was 14.3 L and 1.19 L in one plowing cycle and one transport cycle, respectively, with final battery SOC values of 60.75% and 60.32%, respectively. Under FA-ECMS, the hybrid farm tractor consumed 13.34 L and 1.13 L in one plowing cycle and one transport cycle, respectively, with final battery SOC values of 60.27% and 60.17%, respectively. The results showed that, with the introduction of a fuzzy PI controller to dynamically adjust the equivalence factor, the overall fuel consumption was reduced by 6.71% and 5.04%, respectively, and the battery power maintenance performance was improved. The designed control strategy could achieve a more reasonable power distribution between the engine and motor while maintaining the balance of the battery SOC.

Keywords: hybrid agricultural tractor; hydro-mechanical continuously variable transmission; fuzzy adaptive; equivalent fuel consumption minimization strategy; energy saving (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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