Receding horizon control strategy for an electric vehicle with dual-motor coupling system in consideration of stochastic vehicle mass

Aiming at the unreasonable determination of the power coupling device speed ratio and the power battery capacity in the initial design stage of the dual-motor electric tractor, a dual-motor drive system is designed, and a parameter optimization method based on driving cycles (POMBDC) is proposed. By analyzing the driving characteristics requirements and actual working conditions of the tractor, the dynamic model of the dual-motor drive system under different working modes is established, and the parameters of the dual-motor, transmission and maximum service mass are designed. On this basis, based on the driving cycles and aiming at the lowest power consumption, the POMBDC is formed, this method can collaboratively optimize the power coupling device speed ratio and the power battery capacity. In order to verify the rationality of the POMBDC, the instantaneous optimization-constant speed ratio design method (IO-CSRDM), rule-optimization speed ratio design method (R-OSRDM) and rule-constant speed ratio design method (R-CSRDM) are developed as comparison methods, and simulation experiments are carried out. Under plowing conditions, the power battery capacity of the POMBDC is 3.08%, 5.71%, and 8.73% lower than those of the IO-CSRDM, R-OSRDM, and R-CSRDM, respectively. The power consumption resulting from the POMBDC is reduced by 3.11%, 5.74%, and 8.8%, compared with those of the IO-CSRDM, R-OSRDM and R-CSRDM, respectively. Under rotary tillage conditions, the power battery capacity of the POMBDC is 6%, 8.64%, and 11.11% lower than those of the IO-CSRDM, R-OSRDM, and R-CSRDM, respectively. The power consumption resulting from the POMBDC is reduced by 6.05%, 8.66%, and 11.13%, compared with those of the IO-CSRDM, R-OSRDM and R-CSRDM, respectively. The POMBDC can effectively increase the operating mileage of pure electric tractors and reduce costs.

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“…This paper adopts the commonly used internal resistance model in the parameter design of electric vehicles as the battery model [25].…”

Section: Power Battery Modelmentioning

confidence: 99%

Design and optimization of dual-motor electric tractor drive system based on driving cycles

et al. 2023

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“…Since the HEB runs on the fixed city bus route, the vehicle mass may be changed at bus stations due to the obvious stochastic distribution characteristic of passengers in different bus stations. 48 Therefore, a vehicle mass estimation method together with a demand torque predictive method is proposed in this paper.…”

Section: Optimal Control Problem Formulationand Solutionmentioning

confidence: 99%

A stochastic optimal energy management strategy considering battery health for hybrid electric bus

Cui

Liu

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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The problem of battery health coupled with energy management brings a considerable challenge to the hybrid electric bus. To address this challenge, three contributions are made to realize optimal energy management control while prolonging battery life. First, a semi-empirical aging model of lithium iron phosphate battery is built and identified by the data fitting method, based on the battery cycling test. Besides, a severity factor map is constructed by employing the proposed aging model to characterize the relative aging of the battery under different operating conditions. Second, to make the driver demand torque more appropriate for statistical prediction, a Markov chain is formulated to predict driving behavior and also a stochastic vehicle mass estimation method is proposed to assist the prediction of required torque. Then, a stochastic multi-objective optimization problem is formulated by taking the severity factor map as a battery degradation criterion, where minimized battery degradation and fuel consumption can be simultaneously realized. Finally, a stochastic model predictive control strategy that considers battery health is established. Both simulation and hardware-in-loop tests are performed. The results demonstrate that fuel economy and battery degradation can be improved by 16.73% and 13.8% compared with rule-based strategy, respectively.

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“…With the increasing popularity of electric vehicle (EV), EMT offers great potential in enhancing the speed and toque range of EV and letting driving motor consistently work in high efficiency area [7]. Because the torque and speed of EV's motor can be controlled precisely, the clutch is canceled [8]- [10]. Meanwhile, some types of hybrid electrical vehicle (HEV) also adopt the solution of using EMT The associate editor coordinating the review of this manuscript and approving it for publication was Ding Zhai.…”

Section: Introductionmentioning

confidence: 99%

Multi-Stage Gear Shifting Control Scheme for Electric Mechanical Transmission: Design and Experiment

et al. 2019

Self Cite

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Electric mechanical transmission (EMT) is a low-cost production for the electric vehicle to expend its torque and speed. Gear shifting is the essential function of EMT, but it is a multi-stage process with nonlinearity and uncertainty. In practice, gear shifting control is a difficult problem because of the bad consistency and large shift shock. Hence, a single control method is hard to solve it with satisfying performance. In this paper, motivated by the analysis of experimental results, a novel multi-stage gear shifting control scheme is proposed to improve shifting position tracking performance and decrease shift shock. First, the entire process is divided into three stages and each stage is modeled based on historical data and theoretical analysis. Then, a multi-stage scheme is designed, which is composed of iterative learning control (ILC), linear quadratic regulator (LQR), and H 2 control based on Takagi and Sugeno (T-S) model corresponding to each stage. Finally, the feasibility and effectiveness of the proposed scheme are verified by bench experiments, which might provide guides for the engineering application of the EMT.

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Receding horizon control strategy for an electric vehicle with dual-motor coupling system in consideration of stochastic vehicle mass

Cited by 4 publications

References 28 publications

Design and optimization of dual-motor electric tractor drive system based on driving cycles

Design and optimization of dual-motor electric tractor drive system based on driving cycles

A stochastic optimal energy management strategy considering battery health for hybrid electric bus

Multi-Stage Gear Shifting Control Scheme for Electric Mechanical Transmission: Design and Experiment

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