Optimization-based Assessment of Automatic Transmission Double-transition Shift Controls
Control Engineering Practice, Vol. 76, pp. 155–1662018In the new generation of torque converter automatic transmissions (ATs), characterized by a high number of gears, multi-step gear shifts may be executed frequently in order to improve the driving performance. They include double-transition shifts (DTSs), which require close coordination between multiple control inputs (e.g. torque capacities of four clutches and engine torque). The previously developed AT control trajectory optimization tool is utilized in this paper for the purpose of DTS control optimization including engine torque control. With the aim to gain insights into optimal control action and coordination, six different DTS control strategies are proposed and assessed. These strategies are incorporated into the optimization problem formulation through additional, shift phase-related constraints that the optimization algorithm needs to satisfy. In this way, control strategies with different degrees of complexity and applicability can be quantitatively assessed in terms of achievable shift performance. The proposed strategies have been examined on an example of characteristic DTS downshift of an advanced 10-speed AT. Based on the summarized optimization results obtained for different levels of clutch energy loss penalization, it has been found that the strategy characterized with quick release of the off-going clutches can provide an optimal compromise between shift comfort performance and energy loss reduction. automatic transmission; double-transition shift; control; assessment; optimization
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Control Engineering Practice, Vol. 76, pp. 155–166
2018
Cited by 24
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[1] Review on Modelling the Life Span of a Rubber V-Belt in Industrial Machinery🔗2024 IEEE 5th International Conference on Electro-Computing Technologies for Humanity (NIGERCON), 2024
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[2] Adaptive coordinated control strategy for improving shift quality under different operating conditions🔗Proceedings of the Institution of mechanical engineers. Part D, journal of automobile engineering, 2024
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[3] Gearshift Overlap for Multistep Downshift of Automatic Transmissions Based on Iterative Learning Control🔗IEEE/ASME transactions on mechatronics, 2024
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[4] Controller Design for Electrohydraulic Actuator of Heavy-Duty Automatic Transmission Using Model Predictive Control Algorithm🔗IEEE Transactions on Transportation Electrification, 2023
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[5] Multi-objective parameter optimization strategy based on engine coordinated control for improving shifting quality🔗Advances in Mechanical Engineering, 2023
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[7] Surrogate-assisted multi-objective optimization for control parameters of adjacent gearshift process with multiple clutches🔗Control Engineering Practice, 2023
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[9] Clutch Control Timing Optimization for Adjacent Gearshift Process with Multiple Clutches Based on Adaptive Kriging Surrogate Model🔗2022 6th CAA International Conference on Vehicular Control and Intelligence (CVCI), 2022
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[10] Bond Graph-Based Approach to Modeling Variable-Speed Gearboxes with Multi-Type Clutches🔗Applied Sciences, 2022
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[14] H-Infinity Shifting Control in a Dual-Speed Transmission for Electric Vehicle🔗International journal of automotive technology, 2021
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[15] Upshift optimization control of dedicated hybrid transmission with P2 configuration🔗Vehicle System Dynamics, 2020
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[18] Trajectory optimization with constraints for alpine skiers based on multi-phase nonlinear optimal control🔗Frontiers of Information Technology & Electronic Engineering, 2020
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[20] Coordinate Receding Horizon Control for the Power-Shift Process of Multispeed Electric Vehicles🔗IEEE Transactions on Vehicular Technology, 2020
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[21] Multi-objective parameter optimization of control profiles for automatic transmission double-transition shifts🔗Control Engineering Practice, 2019
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[22] A modularization method of dynamic system modeling for multiple planetary gear trains transmission gearbox🔗Mechanism and Machine Theory, 2019
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[23] Analysis Of Heat Transfer Performance Of Thermal Suit Based On Fourier Law🔗Chinese Control and Decision Conference, 2019