Energy recovery strategy for regenerative braking system of intelligent four‐wheel independent drive electric vehicles
Abstract Regenerative braking system can recovery energy in various electric vehicles. Considering large computation load of global optimization methods, most researches adopt instantaneous or local algorithms to optimize the recuperation energy, and incline to study straight deceleration processes....
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
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Wiley
2021-01-01
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Series: | IET Intelligent Transport Systems |
Subjects: | |
Online Access: | https://doi.org/10.1049/itr2.12009 |
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author | Liang Li Xianyao Ping Jialei Shi Xiangyu Wang Xiuheng Wu |
author_facet | Liang Li Xianyao Ping Jialei Shi Xiangyu Wang Xiuheng Wu |
author_sort | Liang Li |
collection | DOAJ |
description | Abstract Regenerative braking system can recovery energy in various electric vehicles. Considering large computation load of global optimization methods, most researches adopt instantaneous or local algorithms to optimize the recuperation energy, and incline to study straight deceleration processes. However, uncertain drivers' intentions limit the potential exploration of economy improvement, and simple test conditions do not reflect the complexity of actual driving cycles. Herein, an innovative control architecture is designed for intelligent vehicles to overcome these challenges to some extent. Compared with traditional vehicles, driverless ones would eliminate drivers' interferences, and have more freedoms to optimize energy recovery, route tracking and dynamics stability. Specifically, a series regenerative braking system is designed, and then a three‐level control architecture is first proposed to coordinate three performances. In the top layer, some rules with maximum recuperation energy is exploited off‐line for optimising the velocity and control commands on‐line. In the middle layer, local algorithm is used to track the commands and complex routes for optimal energy from a global perspective. In the bottom layer, hydraulic and regenerative toques are allocated. Tests are conducted to demonstrate the effectiveness of the design and control schemes. |
first_indexed | 2024-04-11T21:00:14Z |
format | Article |
id | doaj.art-74cad7fae11a420a980684c8b758ad69 |
institution | Directory Open Access Journal |
issn | 1751-956X 1751-9578 |
language | English |
last_indexed | 2024-04-11T21:00:14Z |
publishDate | 2021-01-01 |
publisher | Wiley |
record_format | Article |
series | IET Intelligent Transport Systems |
spelling | doaj.art-74cad7fae11a420a980684c8b758ad692022-12-22T04:03:32ZengWileyIET Intelligent Transport Systems1751-956X1751-95782021-01-0115111913110.1049/itr2.12009Energy recovery strategy for regenerative braking system of intelligent four‐wheel independent drive electric vehiclesLiang Li0Xianyao Ping1Jialei Shi2Xiangyu Wang3Xiuheng Wu4State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing ChinaState Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing ChinaDepartment of Mechanical Engineering University College London London UKState Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing ChinaState Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing ChinaAbstract Regenerative braking system can recovery energy in various electric vehicles. Considering large computation load of global optimization methods, most researches adopt instantaneous or local algorithms to optimize the recuperation energy, and incline to study straight deceleration processes. However, uncertain drivers' intentions limit the potential exploration of economy improvement, and simple test conditions do not reflect the complexity of actual driving cycles. Herein, an innovative control architecture is designed for intelligent vehicles to overcome these challenges to some extent. Compared with traditional vehicles, driverless ones would eliminate drivers' interferences, and have more freedoms to optimize energy recovery, route tracking and dynamics stability. Specifically, a series regenerative braking system is designed, and then a three‐level control architecture is first proposed to coordinate three performances. In the top layer, some rules with maximum recuperation energy is exploited off‐line for optimising the velocity and control commands on‐line. In the middle layer, local algorithm is used to track the commands and complex routes for optimal energy from a global perspective. In the bottom layer, hydraulic and regenerative toques are allocated. Tests are conducted to demonstrate the effectiveness of the design and control schemes.https://doi.org/10.1049/itr2.12009Optimisation techniquesRoad‐traffic system controlOptimisationMechanical componentsVehicle mechanicsOptimisation techniques |
spellingShingle | Liang Li Xianyao Ping Jialei Shi Xiangyu Wang Xiuheng Wu Energy recovery strategy for regenerative braking system of intelligent four‐wheel independent drive electric vehicles IET Intelligent Transport Systems Optimisation techniques Road‐traffic system control Optimisation Mechanical components Vehicle mechanics Optimisation techniques |
title | Energy recovery strategy for regenerative braking system of intelligent four‐wheel independent drive electric vehicles |
title_full | Energy recovery strategy for regenerative braking system of intelligent four‐wheel independent drive electric vehicles |
title_fullStr | Energy recovery strategy for regenerative braking system of intelligent four‐wheel independent drive electric vehicles |
title_full_unstemmed | Energy recovery strategy for regenerative braking system of intelligent four‐wheel independent drive electric vehicles |
title_short | Energy recovery strategy for regenerative braking system of intelligent four‐wheel independent drive electric vehicles |
title_sort | energy recovery strategy for regenerative braking system of intelligent four wheel independent drive electric vehicles |
topic | Optimisation techniques Road‐traffic system control Optimisation Mechanical components Vehicle mechanics Optimisation techniques |
url | https://doi.org/10.1049/itr2.12009 |
work_keys_str_mv | AT liangli energyrecoverystrategyforregenerativebrakingsystemofintelligentfourwheelindependentdriveelectricvehicles AT xianyaoping energyrecoverystrategyforregenerativebrakingsystemofintelligentfourwheelindependentdriveelectricvehicles AT jialeishi energyrecoverystrategyforregenerativebrakingsystemofintelligentfourwheelindependentdriveelectricvehicles AT xiangyuwang energyrecoverystrategyforregenerativebrakingsystemofintelligentfourwheelindependentdriveelectricvehicles AT xiuhengwu energyrecoverystrategyforregenerativebrakingsystemofintelligentfourwheelindependentdriveelectricvehicles |