Design of slip-based traction control system for EV and validation using co-simulation between Adams and Matlab/Simulink

Saha, Sudipta; Amrr, Syed Muhammad

doi:10.1177/0037549719897834

Cited by 15 publications

(11 citation statements)

References 32 publications

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“…The control target modifying coefficient K e is determined as formula (15) in this study. In addition, N is the number of steps of the inner control loop, and it is determined as the formula (16).…”

Section: Modifying Control Targetmentioning

confidence: 99%

“…[9][10][11] In addition, sliding mode control is proposed to improve the robustness and stability of the anti-slip control. [12][13][14][15][16] In recent years, Model Predictive Control (MPC) is applied to the anti-slip control of distributed motor vehicles to achieve slip control, lateral stability, and rollover prevention. 17 In addition, explicit nonlinear MPC is also proposed for electric vehicle traction control to improve dynamic performance 18 and hybrid MPC control is also applied to the vehicle traction control.…”

Section: Introductionmentioning

confidence: 99%

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An anti-slip control strategy with modifying target and torque reallocation for heavy in-wheel motor vehicle

Wang

Yuan

Chen

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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In-wheel motors are used in heavy vehicles such as buses and trucks to improve efficiency and compactness, the safety of which is particularly important. Anti-slip control is applied to road vehicles to improve the active safety performance, and it is necessary for heavy in-wheel motor vehicles. However, the experiment results in this study show that the response delay of motors on the heavy vehicle is larger than that of the passenger car, and the vehicle mass often changes, which brings drawbacks to the rapidity and stability of its dynamics control. For these problems, an improved Proportional-Derivative Control with a modifying desired wheel rotational speed is proposed for the slip regulation. The modifying control target is intended to mitigate steady tracking error, the role of which is similar to the traditional Integral Control. The desired wheel rotational speed is modified through the response in the current period, and then is set as the new target in the next period. Because the anti-slip control of driving wheels on each side is independent, the torque reallocation strategy is introduced to coordinate with the yaw control and take the yaw dynamics into account, which therefore improves the lateral stability. To avoid the excessive driving torque increment causing the slipping phenomenon again, after the anti-slip control finishing, a transition process is applied. Finally, simulations and real vehicle experiments are conducted to verify the effectiveness and flexibility of the control algorithm, and the results indicate that the control strategy has an expected performance.

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Section: Modifying Control Targetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An anti-slip control strategy with modifying target and torque reallocation for heavy in-wheel motor vehicle

Wang

Yuan

Chen

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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show abstract

“…Unlike the corrective yaw moment which is the output of the controller using the LQR, in this case the output of the system is defined to be the value of the hydraulic pressure of the braking system. The output variable of the hydraulic pressure of the sliding mode controller is defined as: (10) where , while and…”

Section: T a B L Ementioning

confidence: 99%

“…This model is used in [2] and [5], as prime model for research, while this model can be used also as reference model in cosimulation analysis. Using a virtual vehicle model in ADAMS and a reference bicycle model created in Matlab/Simulink is analyzed in [8], [10] and [15].…”

mentioning

confidence: 99%

Implementation of Advanced Control Methods for Improved Vehicle Dynamics and Safety Using Co-Simulation Approach

Čangoski¹,

Ðurkov²,

Jordanoska³

2020

MESJ

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The increasing application of mechatronic devices in everyday life increases the demands for higher reliability and safety in order to achieve more sustainable systems. Inspired by the enormous efforts put in decreasing the number of accidents on the roads which is attributed to implementation of improved mechatronic systems, a controller for improved vehicle dynamics was created and comparison between two advanced control methods was made. Improved vehicle dynamics and stability control system is mandatory for most vehicles, and in order to make contribution in this field, a cascade controller for selective wheel braking control is implemented in a virtual 3D vehicle model. By using sliding mode control (SMC) and Linear Quadratic Regulator (LQR) as adopted control methods, an improved vehicles dynamics is achieved and also a more reliable system is created due to the adaptiveness of the control strategies. Using co-simulation approach involving ADAMS/Car and Matlab/Simulink, results for standardized vehicle maneuvers are obtained and the benefits of the proposed controllers are analyzed.

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“…A co-simulation analysis is also conducted in [11] where slip-based traction controller is implemented in order to optimize the traction controller of an electric vehicle. In the paper, the SMC controllers are implemented in vehicle dynamics control, AFS and ARS systems.…”

Section: Introductionmentioning

confidence: 99%

Improving vehicle dynamics employing individual and coordinated sliding mode control in vehicle stability, active front wheel steering and active rear wheel steering systems in co-simulation environment

Changoski

Gjurkov

Jordanoska

2022

IOP Conf. Ser.: Mater. Sci. Eng.

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The goal for the future, safer and more sustainable transportation leads to implementation of many advanced systems in vehicles. In this paper, a vehicle model with stability control system that uses the braking system is regarded as a base active vehicle. Two alternative vehicle models are considered where this system is combined and integrated with active front wheel steering (AFS) and active rear wheel steering (ARS) system, separately. For the purpose of this research, 3D virtual vehicle models based on a B-segment vehicle were created in ADAMS/Car. As a research tool, a co-simulation approach between ADAMS/Car and MATLAB/Simulink was used. Several sliding mode controllers (SMC) have been proposed and implemented in MATLAB/Simulink in order to analyse the potential improvements of the vehicle dynamics due to the integration and coordination of these systems. In the same MATLAB/Simulink environment, a reference 2DOF nonlinear bicycle model was used. The vehicle models were simulated in driving scenarios based on standardized ISO 7401 test procedures. The scenarios include situations where the passive vehicle loses its stability or fails to complete the manoeuvre while the vehicles with stability control or integrated control systems successfully complete it.

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Design of slip-based traction control system for EV and validation using co-simulation between Adams and Matlab/Simulink

Cited by 15 publications

References 32 publications

An anti-slip control strategy with modifying target and torque reallocation for heavy in-wheel motor vehicle

An anti-slip control strategy with modifying target and torque reallocation for heavy in-wheel motor vehicle

Implementation of Advanced Control Methods for Improved Vehicle Dynamics and Safety Using Co-Simulation Approach

Improving vehicle dynamics employing individual and coordinated sliding mode control in vehicle stability, active front wheel steering and active rear wheel steering systems in co-simulation environment

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