Research on characteristic parameter selection and attention-GRU-based model for braking intention identification

Li, Xuebo; Ma, Jian; Zhao, Xuan; Wang, Lu

doi:10.1177/09544070221145474

Cited by 3 publications

(3 citation statements)

References 49 publications

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“…IPMSM possesses advantages such as high power density and strong overload capacity [1,2], which is widely used in the field of new energy vehicles [3][4][5][6]. Sensorless control technology has emerged as a prominent research area [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Sensorless Control Strategy for Interior Permanent Magnet Synchronous Motors in the Full-Speed Section

Wang,

Ma,

Zhao

et al. 2023

Energies

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Along with the advancement of modern control technology, electric vehicles have gradually become the leading force in the development of the automobile industry. Interior permanent magnet synchronous motors (IPMSMs) have gradually become a mainstream electric vehicle drive component due to their high power density and excellent controllability. This type of motor can form a high-precision closed-loop control system with position sensors, which improves the overall performance. However, the operating conditions are complicated, and position sensor failure can easily occur, which reduces the stability of the motor system. For the fault-tolerant control problem of position sensor failure, pulse high-frequency voltage injection and an improved sliding mode observer (SMO) are employed to achieve the sensorless control of both the low-speed and medium-high-speed sections of the electric motor. Combining the advantages of high-frequency voltage injection in the low-speed section with a high accuracy of position estimation and the advantages of improved SMO in the high-speed section with low computational volume, the composite sensorless control strategy is proposed for IPMSM in the full-speed section. Secondly, an improved SMO using a segmented composite function as the control function is proposed to improve the robustness of the system. It is proposed to address the issue of the smooth transition between the low-speed section and the medium- and high-speed section by using linear weighting. Finally, in order to validate the accuracy of the sensorless control technology, a rapid control prototype of IPMSMs based on Speedgoat is constructed by using a semi-physical simulation system. The efficacy of the control algorithms in the low-speed section, high-speed section and transition interval is verified.

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Section: Introductionmentioning

confidence: 99%

Sensorless Control Strategy for Interior Permanent Magnet Synchronous Motors in the Full-Speed Section

Wang,

Ma,

Zhao

et al. 2023

Energies

Self Cite

View full text Add to dashboard Cite

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“…They introduced the attention mechanism into the proposed model to improve identification accuracy by capturing valuable feature information. The proposed mechanism can achieve the accuracy of slight braking, normal braking, and emergency braking by 96.3%, 95.8%, and 100%, respectively [9]. Lv et al classified braking intensity into three levels and proposed a novel continuous observation method based on artificial neural networks to quantitatively analyze and identify the brake intensity using the prior determined features of the vehicle states.…”

Section: Introductionmentioning

confidence: 99%

Braking Intention Identification Strategy of Electric Loader Based on Fuzzy Control

Ye,

Wu,

Lin

2023

Applied Sciences

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As a widely-used construction machinery, the electric loader has the potential to recover braking energy due to its large mass and frequent starts and stops. Identifying braking intention accurately is the foundation of braking energy recovery. The typical braking condition of an electric loader is analyzed; the braking intention is divided into sliding brake, mild braking, moderate braking, and emergency braking. A large number of braking data were collected under different braking intentions, which are used as the basis for fuzzy control variable partitioning, fuzzy controller parameter setting and fuzzy control rule formulation. The control strategies of deceleration intention identification based on accelerator pedal, braking intention identification based on brake pedal and sliding brake intention identification are proposed in this paper, respectively. This paper takes the hydraulic brake pressure as a feedback parameter, even if there is hysteresis or failure based on the intention of pedal identification, the system can still provide sufficient braking strength to ensure the braking safety. The AMESim(R12)-Matlab/Simulink co-simulation model and prototype are built to verify the feasibility of the control strategy under different braking intention identification. The results show that the braking strength under stronger braking intention can satisfy the braking demand whether at a speed of 2 m/s or 12 m/s, which ensures the safety of emergency braking, and the electric loader can provide stable braking strength under different braking intention and different speed. This has good braking stability.

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“…Hongyu Zheng optimized the regenerative power state of four hub motors by reducing the participation of mechanical braking and improved the braking energy recovery rate under the premise of ensuring braking performance [13] . Xianxu Bai studied the critical velocity of regenerative braking based on 14 typical urban driving cycles to maximize the use of braking energy [14] . Regarding the impact of braking comfort for in-wheel motor-driven electric vehicles, Jin Xianjian proposed a μ-Synthesis Methodology and a robust finite frequency H∞ control strategy for the in-wheel motoractive suspension system, effectively improving vibration performance and ride comfort [15,16] .…”

Section: Introductionmentioning

confidence: 99%

Research on Composite Braking Control Strategy of Four-Wheel-Drive Electric Vehicles With Multiple Motors Based on Braking Energy Recovery Optimization

Xu,

Li,

Zhang

et al. 2023

IEEE Access

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Four-wheel-drive system with multiple motors has been one of the important development trends of electric vehicles, which has an important impact on the regenerative braking of electric vehicles. Aiming at the configuration characteristics of a composite braking system for the four-wheel-drive electric vehicle with multiple motors, this paper proposed a novelty composite braking control strategy based on braking energy recovery optimization. Firstly, the characteristics and constraints of braking dynamics of fourwheel-drive electric vehicles with multiple motors were analyzed. Secondly, the composite braking control strategy to optimize braking energy recovery was developed. The control strategy mainly optimized the motor braking of the front and rear axle according to the braking energy recovery efficiency within the range of motor braking to maximize the recovery of braking energy. And the motor and hydraulic braking forces were concertedly distributed to improve braking stability. Finally, the semi-physical simulation platform is used to verify the composite braking control strategy under single braking conditions and CLTC-P cycle condition. The test results demonstrate that the composite braking control strategy proposed in this paper can effectively improve braking energy recovery and braking stability.

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Research on characteristic parameter selection and attention-GRU-based model for braking intention identification

Cited by 3 publications

References 49 publications

Sensorless Control Strategy for Interior Permanent Magnet Synchronous Motors in the Full-Speed Section

Sensorless Control Strategy for Interior Permanent Magnet Synchronous Motors in the Full-Speed Section

Braking Intention Identification Strategy of Electric Loader Based on Fuzzy Control

Research on Composite Braking Control Strategy of Four-Wheel-Drive Electric Vehicles With Multiple Motors Based on Braking Energy Recovery Optimization

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