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  • SAGE Publications  (8)
  • Chen, Long  (8)
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  • SAGE Publications  (8)
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  • 1
    Online Resource
    Online Resource
    Speed-dependent coordinated control of differential and assisted steering for in-wheel motor driven electric vehicles
    SAGE Publications ; 2018
    In:  Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering Vol. 232, No. 9 ( 2018-08), p. 1206-1220
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, SAGE Publications, Vol. 232, No. 9 ( 2018-08), p. 1206-1220
    Abstract: In this paper, we present a coordinated control system of differential and assisted steering for in-wheel motor driven (IMD) electric vehicles (EVs) with two independent front-wheel drives. An electric differential (ED) control strategy is proposed to track the expected yaw rate based on sliding mode control (SMC). Meanwhile, to realize differential drive assisted steering (DDAS), a variable speed integral PID controller is used to follow the ideal steering wheel torque. The impacts of the coupling with the ED and DDAS systems on EVs are analyzed, and a coordinated control system with adaptive weighting dependent on vehicle speed is designed. Results of the simulation on the CarSim-Simulink joint platform for IMD EVs model show that the proposed coordinated control approach can effectively reduce the torque of a steering wheel while ensuring the vehicle’s stability. Finally, road testing results of IMD EVs are demonstrated to be comparable with joint simulations, indicating the correctness of this solution.
    Type of Medium: Online Resource
    ISSN: 0954-4070 , 2041-2991
    URL: Article
    DOI: 10.1177/0954407017728189
    RVK:
    ZO 4200
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
    detail.hit.zdb_id: 2032754-7
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Coordination control method of autonomous ground electric vehicle for simultaneous trajectory tracking and yaw stability control
    SAGE Publications ; 2023
    In:  Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering Vol. 237, No. 5 ( 2023-04), p. 941-957
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, SAGE Publications, Vol. 237, No. 5 ( 2023-04), p. 941-957
    Abstract: A hierarchical trajectory tracking and yaw stability combined control strategy of autonomous ground vehicle within-wheel motor is proposed in this paper to achieve simultaneous and accurate trajectory tracking and vehicle yaw stability control. A trajectory-tracking controller is designed on the basis of model predictive control algorithm, and the ideal front-wheel steering angle requirement is calculated to follow the referenced trajectory. In order to improve the accuracy of vehicle steering control, a vehicle steering controller is designed based on high-order sliding mode control method, in which the control demand of front-wheel steering angle is satisfied by real-time torque control of vehicle steering motor. Simultaneously, a double power reaching rate-based sliding mode control method is applied to design the vehicle yaw stability controller, in which the yaw moment control requirement is met by an optimal oriented tire force allocation algorithm. The simulation and experiment results show that the presented control method can improve the accuracy and real-time performance of trajectory tracking control while ensuring vehicle yaw stability.
    Type of Medium: Online Resource
    ISSN: 0954-4070 , 2041-2991
    URL: Article
    DOI: 10.1177/09544070221087485
    RVK:
    ZO 4200
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2032754-7
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Design and analysis of herringbone gear with sixth-order transmission error based on meshing vibration optimization
    SAGE Publications ; 2017
    In:  Advances in Mechanical Engineering Vol. 9, No. 6 ( 2017-06), p. 168781401770435-
    Details
    In: Advances in Mechanical Engineering, SAGE Publications, Vol. 9, No. 6 ( 2017-06), p. 168781401770435-
    Type of Medium: Online Resource
    ISSN: 1687-8140 , 1687-8140
    URL: Article
    DOI: 10.1177/1687814017704359
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2017
    detail.hit.zdb_id: 2501620-9
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    Online Resource
  • 4
    Online Resource
    Online Resource
    Expected yaw rate–based trajectory tracking control with vision delay for intelligent vehicle
    SAGE Publications ; 2020
    In:  Science Progress Vol. 103, No. 3 ( 2020-07), p. 003685042093427-
    Details
    In: Science Progress, SAGE Publications, Vol. 103, No. 3 ( 2020-07), p. 003685042093427-
    Abstract: Accurate and real-time position of preview point is significant to trajectory tracking control of vision-guided intelligent vehicle. The unavoidable delay of road automatic identification system weakens trajectory tracking control performance, and even deteriorates the vehicle stability. Therefore, a compensator for the delay of road automatic identification system was proposed which combines the current statistical model and adaptive Kalman predictor to estimate the state of preview point position. The trajectory tracking sliding mode controller of intelligent vehicle is established through a 2–degrees of freedom vehicle dynamic model and motion model by using MATLAB/Simulink and CarSim. The trajectory tracking performance under 20–100 ms delay is analyzed. The simulation results show that the trajectory tracking performance of intelligent vehicle will be affected by the delay of road automatic identification system, reducing tracking accuracy. And when the delay is too large, it will deteriorate the vehicle stability and safety. In addition, the simulation results also verify the effectiveness of current statistical–adaptive Kalman predictor compensator at different delays.
    Type of Medium: Online Resource
    ISSN: 0036-8504 , 2047-7163
    URL: Article
    DOI: 10.1177/0036850420934274
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
    detail.hit.zdb_id: 2483680-1
    detail.hit.zdb_id: 2199376-2
    SSG: 11
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    Online Resource
  • 5
    Online Resource
    Online Resource
    Analysis and optimization of energy efficiency for an electric vehicle with four independent drive in-wheel motors
    SAGE Publications ; 2018
    In:  Advances in Mechanical Engineering Vol. 10, No. 3 ( 2018-03), p. 168781401876554-
    Details
    In: Advances in Mechanical Engineering, SAGE Publications, Vol. 10, No. 3 ( 2018-03), p. 168781401876554-
    Type of Medium: Online Resource
    ISSN: 1687-8140 , 1687-8140
    URL: Article
    DOI: 10.1177/1687814018765549
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
    detail.hit.zdb_id: 2501620-9
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    Online Resource
  • 6
    Online Resource
    Online Resource
    Adaptive coordination control strategy for path-following of DDAEV with neural network based moving weight coefficients
    SAGE Publications ; 2023
    In:  Transactions of the Institute of Measurement and Control Vol. 45, No. 7 ( 2023-04), p. 1282-1297
    Details
    In: Transactions of the Institute of Measurement and Control, SAGE Publications, Vol. 45, No. 7 ( 2023-04), p. 1282-1297
    Abstract: This paper presents an adaptive coordination control strategy for path-following of distributed drive autonomous electric vehicles (DDAEV). A model predictive control (MPC) algorithm is used to realize path-following through autonomous steering, where the prediction time is adaptive in relation to different driving conditions. Due to the dynamic characteristic of distributed drive vehicle, the differential torque control is also utilized based on the deviation of path to realize path-following. In order to make full use of the advantages of these two path-following methods, coordination control of autonomous steering and differential steering is adopted to improve the transient response speed, flexibility of steering system and path-following performance by setting moving weight coefficients based on neural network. Results of CarSim-Simulink co-simulation and real vehicle experiment both verify that the proposed coordination control can obtain steering flexibility, as well as tracking accuracy and reliability under various driving conditions.
    Type of Medium: Online Resource
    ISSN: 0142-3312 , 1477-0369
    URL: Article
    DOI: 10.1177/01423312221135255
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2025882-3
    SSG: 3,2
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    Online Resource
  • 7
    Online Resource
    Online Resource
    Modeling adaptive preview time of driver model for intelligent vehicles based on deep learning
    SAGE Publications ; 2022
    In:  Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering Vol. 236, No. 2 ( 2022-02), p. 355-369
    Details
    In: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, SAGE Publications, Vol. 236, No. 2 ( 2022-02), p. 355-369
    Abstract: In order to improve the adaptability and tracking performance of intelligent vehicles under complex driving conditions, and simulate the manipulation characteristics of the real driver in the driver–vehicle–road closed-loop system, a kind of adaptive preview time model for intelligent vehicle driver model is proposed. This article builds the intelligent vehicle driver model based on optimal preview control theory and the basic preview time is identified to minimize path error under various conditions based on particle swarm optimization. Then, the ideal compensation preview time is constructed in various conditions and the appropriate factors affecting compensation preview time are filtered out according to correlation analysis. Moreover, the architecture and training procedure of deep network is specified for compensation preview time prediction. Finally, the adaptive preview time is modeled by combining the basic preview time with the compensation preview time and the validity of adaptive preview time model is verified by the driver–vehicle–road closed-loop system under normal and aggressive driving conditions. The results show that the proposed adaptive preview time model can help intelligent vehicles better adapt complex driving conditions and effectively improve the path-following performance.
    Type of Medium: Online Resource
    ISSN: 0959-6518 , 2041-3041
    URL: Article
    DOI: 10.1177/09596518211028372
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
    detail.hit.zdb_id: 2024903-2
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    Online Resource
  • 8
    Online Resource
    Online Resource
    Study of the influence mechanism of pitch deviation on cylindrical helical gear meshing stiffness and vibration noise
    SAGE Publications ; 2017
    In:  Advances in Mechanical Engineering Vol. 9, No. 9 ( 2017-09), p. 168781401772058-
    Details
    In: Advances in Mechanical Engineering, SAGE Publications, Vol. 9, No. 9 ( 2017-09), p. 168781401772058-
    Type of Medium: Online Resource
    ISSN: 1687-8140 , 1687-8140
    URL: Article
    DOI: 10.1177/1687814017720586
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2017
    detail.hit.zdb_id: 2501620-9
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    Online Resource
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