Optimal coordinating gearshift control of a two-speed transmission for battery electric vehicles

Yang, Tianyue; Yang, Haojin; Mo, Wenwei; Zhou, Shilei; Zhang, Nong; Walker, Paul

doi:10.1016/j.ymssp.2019.106521

Cited by 19 publications

(15 citation statements)

References 29 publications

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“…2 . By substituting (16) and (17) into (12) and (13), F cn1 , F cf1 , F cn2 and F cf2 can be obtained respectively. Thus, the combined axial force F czx and the combined circumferential force F czy received by SL from DG can be obtained as follows:…”

Section: ) the Force From The Detent Pinmentioning

confidence: 99%

“…Although CLAMT/NSAMT has many advantages, its shift control is difficult [13]- [16]. Many researchers divide the gear shifting process into five stages: torque unloading, gear disengagement, active synchronization (including speed synchronization and angle synchronization), gear engagement, and torque recovery [17]- [19]. Hongbo et al modeled the essential gear shifting stages and found that the speed synchronization stage and gear engagement stage accounted for a massive proportion in gear-shifting time through experimental tests [20], [21].…”

Section: Introductionmentioning

confidence: 99%

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Modeling and Analysis of Gear Shifting Process of Non-Synchronizer AMT Based on Collision Model

Luo

2021

IEEE Access

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In the gear shifting process of a clutchless automated mechanical transmission (AMT), the potential collision between sleeve and dog gear may increase both vehicle jerk and gear changing duration. Therefore, the gear shifting process's mechanism analysis and dynamic modeling are the essential prerequisites to improve gear shifting quality. This paper analyzes the potential collision between the sleeve and the dog gear which both with concave-convex profiles, the tooth-side chamfer considered. To model the collision process, a fast-determining collision face method based on an intersection map is proposed, and the Monte Carlo method and equivalent depth are employed to calculate the collision stiffness. Then, the stiffness-damping model of the collision process and an 8-degree-of-freedom dynamic model of the gear-shifting system are established. Finally, taking a two-speed clutchless and non-synchronizer automated mechanical transmission (NSAMT) as an example, the established dynamic model of the gear-shifting system is applied, and simulation verification is performed in Matlab/Simulink. The simulation results show that the established model can accurately reflect the changes of forces, speeds, and displacements of sleeve and dog gears during the collision and effectively reflect processes of the disengagement of the sleeve, the speed changes in active synchronization, the engagement of sleeve and gear keeping. Besides, the results also show that the tooth-side chamfer will increase the disengagement time, while it is conducive to gear keeping, and that unloading the drive motor can decrease the disengagement time due to the existence of the tooth-side chamfer.

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Section: ) the Force From The Detent Pinmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling and Analysis of Gear Shifting Process of Non-Synchronizer AMT Based on Collision Model

Luo

2021

IEEE Access

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“…Tian investigated the optimal coordinated gearshift control of a seamless two-speed motortransmission system for EVs. The strategy is developed based on optimal controllers, which is normally used to achieve high-quality gearshift process in the torque phase and inertia phase, respectively [22]. Choi proposed a method for estimating transmission torque, which can adaptively compensate for the changing factors in gearshift process [23].…”

Section: Introductionmentioning

confidence: 99%

Gearshift Control in Engagement Process of Dual-Motor Coaxial Propulsion System for Electric Bus

Lin

et al. 2022

IEEE Access

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Considering single-motor drive system cannot meet the requirements of high-performance electric buses for Beijing Winter Olympics, a dual-motor coaxial propulsion system based on single planet gear set is developed. At the same time, a shift control method based on hierarchical linear quadratic regulator (HLQR) algorithm is designed to improve the poor shift quality caused by the rapid change of output shaft speed in the shift process. In this method, the upper controller adopts robust tracking linear quadratic regulator algorithm to control the speed change rate of the output shaft in the process of gear shifting, so as to reduce the load of gear shifting actuator in the process of gear shifting; the lower controller adopts disturbance suppression linear quadratic regulator algorithm to control the shifting force and improve the adaptability of the system to disturbance conditions Through simulation analysis, the performances of hierarchical linear quadratic regulator algorithm, optimal control algorithm based on variational method and PI algorithm in the process of gear shifting were comparatively analyzed. Simulation results showed that the hierarchical linear quadratic regulator algorithm exhibited a better performance in gear control than the other two algorithms. In addition, a large number of bench test results also proved that compared with PI algorithm, hierarchical linear quadratic regulator algorithm reduced vehicle impact by 19.17% and reduced the shift force by 32.48% in the sacrifice of shift time by 5.03%.

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“…The multi-gear and multi-motor powertrains are widely researched in academia with the motivation of improving the electric vehicle energy economy and dynamic performance. The automated manual transmission (AMT) [4,5], dual clutch transmission (DCT) [6], automatic transmission (AT) [7,8] and continuous variable transmission (CVT) [9,10] have been implemented in electric vehicles.…”

Section: Introductionmentioning

confidence: 99%

Comparison on Energy Economy and Vibration Characteristics of Electric and Hydraulic in-Wheel Drive Vehicles

et al. 2021

Self Cite

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This paper compares the energy economy and vertical vibration characteristics of in-wheel drive electric vehicles (IEVs), in-wheel drive electric hydraulic hybrid vehicles (IHVs) and centralized drive electric vehicles (CEVs). The dynamic programming (DP) algorithm is used to explore the optimal energy consumption of each vehicle. The energy economy analysis shows that the IEV consumes more energy than the CEV due to its relatively lower electric motor efficiency, even with fewer driveline components. The IHV consumes much more energy than the IEV and CEV because of the energy loss in the hydraulic driveline. The vertical vibration analysis demonstrates that both IEV and IHV degrade the vehicle driving comfort due to increased unsprung mass. Taking the advantage of high power density of the hydraulic motor, IHV have less unsprung mass when compared with the IEV, which helps to mitigate the vibration problems caused by increased unsprung mass.

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Optimal coordinating gearshift control of a two-speed transmission for battery electric vehicles

Cited by 19 publications

References 29 publications

Modeling and Analysis of Gear Shifting Process of Non-Synchronizer AMT Based on Collision Model

Modeling and Analysis of Gear Shifting Process of Non-Synchronizer AMT Based on Collision Model

Gearshift Control in Engagement Process of Dual-Motor Coaxial Propulsion System for Electric Bus

Comparison on Energy Economy and Vibration Characteristics of Electric and Hydraulic in-Wheel Drive Vehicles

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