Towards Autonomous Driving: Review and Perspectives on Configuration and Control of Four-Wheel Independent Drive/Steering Electric Vehicles

Hang, Peng; Chen, Xinbo

doi:10.3390/act10080184

Cited by 59 publications

(26 citation statements)

References 145 publications

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“…In the design of the intelligent driving control system, the whole system is often divided into perception layer, decision-making and planning layer, motion control layer, execution layer and so on [23,24]. At present, in DDEVs, LSC is mainly implemented by a hierarchical mechanism, which is generally divided into three layers: vehicle motion state prediction layer, vehicle motion tracking layer, and torque distribution and executive layer [2,3,[25][26][27].…”

Section: Stability-tracking Hierarchical Control Structurementioning

confidence: 99%

“…Due to the simple transmission mode of pure electric vehicles, most of the ADVs use pure electric chassis. In many driving modes of electric vehicles, the distributed driving mode with hub motor drive as the core has unique advantages in enhancing vehicle safety, handling stability and improving vehicle energy efficiency, and has become a hot spot in academic and industrial circles [2,3]. By optimizing the allocation of the driving/braking torque of each wheel, many vehicle active safety technologies can be implemented through this structure, such as Antilock Braking System (ABS), Acceleration Slip Regulation (ASR), Differential Drive Assist Steering (DDAS), Electronic Differential Control (EDC), Four Wheel Steering (4WS), Vehicle Stability Control (VSC), etc., [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Intrinsic Mechanistic of Stability-Tracking Control for Distributed Drive Autonomous Electric Vehicle

Tang

Wang

et al. 2021

Electronics

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For distributed drive autonomous vehicles, adding lateral stability control (LSC) to the trajectory tracking control (TTC) can optimize the distribution of the driving torque of each wheel, so that the vehicle can track the planned trajectory while maintaining stable lateral motion. However, the influence of adding LSC on the TTC system is still unclear. Firstly, a stability-track hierarchical control structure composed of LSC and TTC was established, and the interaction between the two layers was identified as the key of this paper. Then, the Intrinsic Mechanistic framework of the stability-tracking control (STC) was proposed by establishing and analyzing the vehicle dynamic model and control process of two layers. Finally, through simulation experiments, it was found that the change in the curvature of the target trajectory will make the tracking target trajectory and maintaining the lateral stability of the vehicle appear to conflict; in addition, in the LSC layer, the steering characteristics and delay characteristics of different reference models have a greater impact on the lateral stability and trajectory tracking performance; moreover, adjusting the preview time has a more obvious effect on trajectory tracking and lateral stability than the stability correction intensity coefficient.

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Section: Stability-tracking Hierarchical Control Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of Intrinsic Mechanistic of Stability-Tracking Control for Distributed Drive Autonomous Electric Vehicle

Tang

Wang

et al. 2021

Electronics

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show abstract

“…Making full use of the additional degrees of freedom of the 4WS vehicle can independently control the path and attitude of the vehicle, reduce the yaw motion required by the body, and improve the responsiveness of the vehicle heading change [2]. At the same time, the vehicle has better path tracking performance due to the improvement of flexibility [17].…”

Section: Introductionmentioning

confidence: 99%

Optimal Control Method of Path Tracking for Four-Wheel Steering Vehicles

2022

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Path tracking is a key technique for intelligent electric vehicles, while four-wheel steering (4WS) technology is of great significance to improve its accuracy and flexibility. However, the control methods commonly used in path tracking for a 4WS vehicle cannot take full advantage of the additional steering freedom of the 4WS vehicle, because of restricting the relationship between the front and rear wheels steering angle. To address this issue, we derive a kinematic model without the restriction based on the small-angle assumption. Then, the objective function and constraints of system control quantity optimization are designed based on the tracking error model. After the optimization problem is solved in the form of quadratic programming with constraints, the control sequence with the smallest performance index is obtained through rolling optimization. The proposed method is tested on a high-fidelity Carsim/Simulink co-simulation platform and an experimental vehicle. The results show that the standard deviation of the lateral error and the yaw angle error of the algorithm is less than 0.1 m and 3.0°, respectively. Compared with the other two algorithms, the control of the front and rear wheels angle of this method is more flexible and the tracking accuracy is higher.

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“…This requires more than three sensors, which increases the complexity of development. In order to achieve a better driving performance including rollover prevention, four-wheel independent drive/steering electric vehicles (4WID-4WIS EV) have been introduced and discussed [14]. The X-by-wire chassis technique is a critical issue for the successful development of autonomous commercial vehicles in the future, since it does not restrict the autonomous driving platform design.…”

Section: Introductionmentioning

confidence: 99%

“…The X-by-wire chassis technique is a critical issue for the successful development of autonomous commercial vehicles in the future, since it does not restrict the autonomous driving platform design. Future commercial vehicle design can be realized through integrated X-by-wire modules of 4WID-4WIS EV by considering rollover prevention control while ensuring sufficient space inside the vehicle [14].…”

Section: Introductionmentioning

confidence: 99%

Rollover Index for Rollover Mitigation Function of Intelligent Commercial Vehicle’s Electronic Stability Control

2021

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This paper describes a rollover index for detection or prediction of impending rollover in different driving situations using minimum sensor signals which can be easily obtained from an electronic stability control (ESC) system. The estimated lateral load transfer ratio (LTR) was used as a rollover index with only limited information such as the roll state of the vehicle and some constant parameters. A commercial vehicle has parameter uncertainties because of its load variation. This is likely to affect the driving performance and the estimation of the dynamic state of the vehicle. The main purpose of this paper is to determine the rollover index based on reliable measurements and the parameters of the vehicle. For this purpose, a simplified lateral and vertical vehicle dynamic model was used with some assumptions. The index is appropriate for various situations although the vehicle parameters may change. As part of the index, the road bank angle was investigated in this study, using limited information. Since the vehicle roll dynamics are affected by the road bank angle, the road bank angle should be incorporated, although previous studies ignore this factor in order to simplify the problem. Because it increases or reduces the chances of rollover, consideration of the road bank angle is indispensable in the rollover detection and mitigation function of the ESC system. The performance of the proposed algorithm was investigated via computer simulation studies. The simulation studies showed that the proposed estimation method of the LTR and road bank angle with limited sensor information followed the actual LTR value, reducing the parameter uncertainties. The simulation model was constructed based on a heavy bus (12 tons).

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Towards Autonomous Driving: Review and Perspectives on Configuration and Control of Four-Wheel Independent Drive/Steering Electric Vehicles

Cited by 59 publications

References 145 publications

Analysis of Intrinsic Mechanistic of Stability-Tracking Control for Distributed Drive Autonomous Electric Vehicle

Analysis of Intrinsic Mechanistic of Stability-Tracking Control for Distributed Drive Autonomous Electric Vehicle

Optimal Control Method of Path Tracking for Four-Wheel Steering Vehicles

Rollover Index for Rollover Mitigation Function of Intelligent Commercial Vehicle’s Electronic Stability Control

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