LAPSE:2023.26704v1
Published Article

LAPSE:2023.26704v1
Gear Ratio Optimization along with a Novel Gearshift Scheduling Strategy for a Two-Speed Transmission System in Electric Vehicle
April 3, 2023
Abstract
A novel gearshift scheduling strategy has been framed for a two-speed transmission system in electric vehicles that can save energy during hilly driving and frequently changing driving conditions through efficient electric motor operation. Unlike the traditional approach, the proposed gearshift strategy is based on the preferred vehicle speed range, vehicle acceleration, and road grade to ensure desired vehicle performances with minimum energy consumption. Meanwhile, the vehicle speed range is chosen around the electric motor rated speed, and two gearshift schedules in relation to vehicle acceleration and road grade are developed based on the motor torque generating capacity and efficiency. Appropriate gear is selected through a combined assessment of the required vehicle speed, acceleration, and road grade information. A guideline is developed and explained for the primary gearshift schedule. Next, the gear ratios and gearshift schedules are optimized combinedly in a Simulink environment using the gradient descent method and pattern search method on three driving cycles separately. Depending on the driving scenarios, around 4% to 7.5% energy saving has been experienced through optimization, while the gear ratios and gearshift schedule in relation to the road grade are found to be major contributors to the vehicle economic driving compared to that with the gearshift schedule for vehicle acceleration.
A novel gearshift scheduling strategy has been framed for a two-speed transmission system in electric vehicles that can save energy during hilly driving and frequently changing driving conditions through efficient electric motor operation. Unlike the traditional approach, the proposed gearshift strategy is based on the preferred vehicle speed range, vehicle acceleration, and road grade to ensure desired vehicle performances with minimum energy consumption. Meanwhile, the vehicle speed range is chosen around the electric motor rated speed, and two gearshift schedules in relation to vehicle acceleration and road grade are developed based on the motor torque generating capacity and efficiency. Appropriate gear is selected through a combined assessment of the required vehicle speed, acceleration, and road grade information. A guideline is developed and explained for the primary gearshift schedule. Next, the gear ratios and gearshift schedules are optimized combinedly in a Simulink environment using the gradient descent method and pattern search method on three driving cycles separately. Depending on the driving scenarios, around 4% to 7.5% energy saving has been experienced through optimization, while the gear ratios and gearshift schedule in relation to the road grade are found to be major contributors to the vehicle economic driving compared to that with the gearshift schedule for vehicle acceleration.
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Keywords
electric vehicle, gear ratio optimization, gearshift scheduling strategy, multi-speed transmission, vehicle performances
Subject
Suggested Citation
Ahssan MR, Ektesabi M, Gorji S. Gear Ratio Optimization along with a Novel Gearshift Scheduling Strategy for a Two-Speed Transmission System in Electric Vehicle. (2023). LAPSE:2023.26704v1
Author Affiliations
Ahssan MR: Department of Mechanical Engineering and Product Design Engineering, Swinburne University of Technology, Melbourne 3122, Australia
Ektesabi M: Department of Telecommunications, Electrical, Robotics and Biomedical Engineering, Swinburne University of Technology, Melbourne 3122, Australia
Gorji S: Institute for Future Environments, Queensland University of Technology, Brisbane 4001, Australia [ORCID]
Ektesabi M: Department of Telecommunications, Electrical, Robotics and Biomedical Engineering, Swinburne University of Technology, Melbourne 3122, Australia
Gorji S: Institute for Future Environments, Queensland University of Technology, Brisbane 4001, Australia [ORCID]
Journal Name
Energies
Volume
13
Issue
19
Article Number
E5073
Year
2020
Publication Date
2020-09-28
ISSN
1996-1073
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Original Submission
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PII: en13195073, Publication Type: Journal Article
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LAPSE:2023.26704v1
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https://doi.org/10.3390/en13195073
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