Cornering stability enhancement algorithm for in-wheel electric vehicle

Ha, Hyunuk; Kim, Jongmoo; Lee, Jang-Myung

doi:10.1109/icit.2014.6894907

Cited by 4 publications

(4 citation statements)

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“…Remark 1: Based on the schedulable criterion ( 12) and the expression ( 9), the lower bound of the time buffer size T b can be determined if the priority j sc th of any measurement signal packet in the feedback channel is known. The time buffer size T b should satisfy T b > R worst−case,j sc (13) Remark 2: Conversely, based on the schedulable criterion (12) and the expression ( 9), the lower bound of the priority j sc th of each measurement signal packet can be determined in the design if the time buffer size T b is known. The priority j sc th of each measurement signal packet should satisfy j sc ≤ max(j), j ∈ j|R worst−case,j < T b (14) Combining the expressions (8) and ( 9), the maximum delay in the loop can be rewritten as follows…”

Section: Network Effect Analysis and Schedulingmentioning

confidence: 99%

“…He and Hori [12] studied the integrated ASC and DYC control for AWID-EVs in critical driving condition. Ha et al [13] used the integrated DYC and ASC control to realize a cornering stability enhancement algorithm for AWID-EVs. Youngjin et al [14] proposed an integrated ASC and DYC control strategy using the dynamic curvature of paths to improve the path tracking of AWID-EVs.…”

Section: Introductionmentioning

confidence: 99%

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Reliable Integrated ASC and DYC Control of All-Wheel-Independent-Drive Electric Vehicles Over CAN Using a Co-Design Methodology

Cao

Zhou³

et al. 2019

IEEE Access

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This paper deals with the negative effects of the in-vehicle network on the integrated anti-slip control (ASC) and direct yaw-moment control (DYC) of all-wheel-independent-drive electric vehicles (AWID-EVs). In the integrated control design of the modern AWID-EVs, increasing control components, e.g., sensors, controllers, and actuators, are usually connected via an in-vehicle network, such as a controller area network (CAN), rather than the traditional point-to-point communication. However, the application of CAN would also bring about unexpected problems, e.g., signal asynchrony, multiple-package transmission, and signal delay, which may degrade the control performance and even destroy the stability of the system. This paper presents a co-design methodology to deal with all these challenges caused by CAN and guarantees a satisfactory vehicle dynamics performance. First, a hierarchical structure is designed for the integrated ASC and DYC control of AWID-EVs over CAN, and an active torque distribution strategy based on a well-known maximum transmissible torque estimation approach is adopted. Then, a scheduling-based communication idea is introduced to deal with all these problems caused by CAN. Third, a Lyapunov-based pole assignment theory is applied to estimate the parameter values in the scheduling design and to guarantee the satisfactory dynamic performance of the control system. A generalized linear quadratic regulator controller is designed for the system synthesis to ensure the tracking control of the vehicle. Finally, simulations and preliminary hardware-in-loop tests indicate that the proposed co-design methodology can deal with the negative effects of the in-vehicle network and ensure reliable vehicle dynamics performance.INDEX TERMS All-wheel-independent-drive electric vehicle (AWID-EV), anti-slip control (ASC), direct yaw-moment control (DYC), co-design of scheduling and control, controller area network (CAN).

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Section: Network Effect Analysis and Schedulingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reliable Integrated ASC and DYC Control of All-Wheel-Independent-Drive Electric Vehicles Over CAN Using a Co-Design Methodology

Cao

Zhou³

et al. 2019

IEEE Access

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“…Although they have attracted the attention of researchers [2,3], their validation and verification is predominantly based on simulation in the time domain. A review [4] of current research on traction control and the ABS in electric vehicles summarizes that 65% of papers rely on computer simulations in the time domain to verify the proposed safety algo-rithms.…”

Section: Introductionmentioning

confidence: 99%

“…In simulation models, the torque reference signal is set by a safety control algorithm separately for each electric drive and it is usually assumed to be applied to the wheels without delay [4]. The mechanics of wheels and of vehicles are researched [3,6], without considering details of electric drive phenomena. In other work [7], a detailed model of an induction motor used as an ABS actuator has been built; however, the controller is described and simulated in continuous time.…”

Section: Introductionmentioning

confidence: 99%

Frequency and time domain characteristics of digital control of electric vehicle in-wheel drives

Jarzębowicz

Opaliński

2017

Archives of Electrical Engineering

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Abstract:In-wheel electric drives are promising as actuators in active safety systems of electric and hybrid vehicles. This new function requires dedicated control algorithms, making it essential to deliver models that reflect better the wheel-torque control dynamics of electric drives. The timing of digital control events, whose importance is stressed in current research, still lacks an analytical description allowing for modeling its influence on control system dynamics. In this paper, authors investigate and compare approaches to the analog and discrete analytical modeling of torque control loop in digitally controlled electric drive. Five different analytical models of stator current torque component control are compared to judge their accuracy in representing drive control dynamics related to the timing of digital control events. The Bode characteristics and stepresponse characteristics of the analytical models are then compared with those of a reference model for three commonly used cases of motor discrete control schemes. Finally, the applicability of the presented models is discussed.

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Cornering stability control for vehicles with active front steering system using T-S fuzzy based sliding mode control strategy

Wong

Zhao

et al. 2019

Mechanical Systems and Signal Processing

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Cornering stability enhancement algorithm for in-wheel electric vehicle

Cited by 4 publications

References 0 publications

Reliable Integrated ASC and DYC Control of All-Wheel-Independent-Drive Electric Vehicles Over CAN Using a Co-Design Methodology

Reliable Integrated ASC and DYC Control of All-Wheel-Independent-Drive Electric Vehicles Over CAN Using a Co-Design Methodology

Frequency and time domain characteristics of digital control of electric vehicle in-wheel drives

Cornering stability control for vehicles with active front steering system using T-S fuzzy based sliding mode control strategy

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