How the four wheels should share forces in an optimum cooperative chassis control

Mokhiamar, Ossama; Abé, Masato

doi:10.1016/j.conengprac.2005.03.023

Cited by 103 publications

(41 citation statements)

References 1 publication

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“…One of it is the reduction in vehicle speed that overrules the driver intention [22]. In the recent times, the active yaw control has been a topic of interest and several strategies for side-slip control, DYC and both simultaneously has been reported [21] [23][24][25][26][27][28].…”

Section: A Control Strategiesmentioning

confidence: 99%

“…Apart from these architectures, Research work can be found on model predictive control (MPC) [29]. These techniques are able to suppress the large tracking error arising due to not considering the transient behaviors during the initialization of the manoeuvre [25] [29]. The MPC has also been employed to achieve the autonomous driving mode in electric vehicles [30].…”

Section: A Control Strategiesmentioning

confidence: 99%

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Design and Analysis of DYC and Torque Vectoring using Multiple-Frequency Control Electronic Differential in an Independent Rear Wheel Driven Electric Vehicle

Neroula,

Sharma

2019

IJEAT

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Electric vehicle (EV) are being embraced in recent times as they run on clean fuel, zero tail emission and are environment-friendly. Recent advancements in the field of power electronics and control strategies have made it possible to the advent in the vehicle dynamics, efficiency and range. This paper presents a design for traction control system (TCS) for longitudinal stability and Direct Yaw Control (DYC) for lateral stability simultaneous. The TCS and DYC is based on multiple frequency controlled electronic differential with a simple and effective approach. Along with it, some overviews have been presented on some state of the art in traction control system (TCS) and torque vectoring. The developed technique reduces nonlinearity, multisensory interfacing complexity and response time of the system. This torque and yaw correction strategy can be implemented alongside fuzzy control, sliding mode or neural network based controller. The effectiveness of the control method has been validated using a lightweight neighbourhood electric vehicle as a test platform. The acquired results confirm the versatility of proposed design and can be implemented in any DC motor based TCS/DYC.

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Section: A Control Strategiesmentioning

confidence: 99%

Section: A Control Strategiesmentioning

confidence: 99%

Design and Analysis of DYC and Torque Vectoring using Multiple-Frequency Control Electronic Differential in an Independent Rear Wheel Driven Electric Vehicle

Neroula,

Sharma

2019

IJEAT

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“…The longitudinal slip and tire-side slip angle for each wheel are expressed as follows [34]:

\begin{array}{l} κ_{f l} = \frac{r ω_{w f l}}{v_{x} - t_{f} \overset{ψ}{true}} - 1, κ_{f r} = \frac{r ω_{w f l}}{v_{x} + t_{f} \overset{ψ}{true}} - 1, \\ κ_{r l} = \frac{r ω_{w f l}}{v_{x} - t_{r} \overset{ψ}{true}} - 1, κ_{r r} = \frac{r ω_{w f l}}{v_{x} + t_{r} \overset{ψ}{true}} - 1 \end{array}

\begin{array}{l} α_{f l} = δ_{f} - \frac{v_{y} + l_{f} \overset{ψ}{true}}{v_{x} - t_{f} \overset{ψ}{true}}, α_{f r} = δ_{f} - \frac{v_{y} + l_{f} \overset{ψ}{true}}{v_{x} + t_{f} \overset{ψ}{true}}, \\ α_{r l} = - \frac{v_{y} - l_{r} \overset{ψ}{true}}{v_{x} - t_{r} \overset{ψ}{true}}, α_{r r} = - \frac{v_{y} - l_{r} \overset{ψ}{true}}{v_{x} + t_{r} \overset{ψ}{true}} \end{array}

where

ω_{w}

is the wheel velocity.…”

Section: High-level Fault Diagnosismentioning

confidence: 99%

“…The results are expressed as follows [34]:

\begin{array}{l} F_{z f l} = \frac{m g l_{r}}{2 l} - \frac{m_{s} a_{x} h_{s}}{2 l} - k_{f} \frac{m_{s} a_{y} h_{s}}{t_{f}}, F_{z f r} = \frac{m g l_{r}}{2 l} - \frac{m_{s} a_{x} h_{s}}{2 l} + k_{f} \frac{m_{s} a_{y} h_{s}}{t_{f}}, \\ F_{z r l} = \frac{m g l_{f}}{2 l} + \frac{m_{s} a_{x} h_{s}}{2 l} - k_{r} \frac{m_{s} a_{y} h_{s}}{t_{r}}, F_{z r r} = \frac{m g l_{f}}{2 l} + \frac{m_{s} a_{x} h_{s}}{2 l} + k_{r} \frac{m_{s} a_{y} h_{s}}{t_{r}} \end{array}

where

m_{s}

is the vehicle sprung mass,

l

is the wheel base,

h_{s}

is the sprung mass height,

t_{f, r}

is the vehicle tread,

a_{x}

is the longitudinal acceleration,

a_{y}

is the lateral acceleration,

k_{f}

is the lateral weight-shift distribution on the front wheel, and

k_{r}

is the lateral weight-shift distribution on the rear wheel.…”

Section: High-level Fault Diagnosismentioning

confidence: 99%

Integrated Fault Diagnosis Algorithm for Motor Sensors of In-Wheel Independent Drive Electric Vehicles

Jeon

Lee

2016

Sensors

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An integrated fault-diagnosis algorithm for a motor sensor of in-wheel independent drive electric vehicles is presented. This paper proposes a method that integrates the high- and low-level fault diagnoses to improve the robustness and performance of the system. For the high-level fault diagnosis of vehicle dynamics, a planar two-track non-linear model is first selected, and the longitudinal and lateral forces are calculated. To ensure redundancy of the system, correlation between the sensor and residual in the vehicle dynamics is analyzed to detect and separate the fault of the drive motor system of each wheel. To diagnose the motor system for low-level faults, the state equation of an interior permanent magnet synchronous motor is developed, and a parity equation is used to diagnose the fault of the electric current and position sensors. The validity of the high-level fault-diagnosis algorithm is verified using Carsim and Matlab/Simulink co-simulation. The low-level fault diagnosis is verified through Matlab/Simulink simulation and experiments. Finally, according to the residuals of the high- and low-level fault diagnoses, fault-detection flags are defined. On the basis of this information, an integrated fault-diagnosis strategy is proposed.

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“…The main stages of integrated/coordinated control are depicted in The next stage is a distribution of control demand between four wheels, taking into account tire grip margin of each wheel, normal force distribution, power minimization and other objectives. Several solutions for force allocation are proposed in [11,34,35].…”

Section: Overview Of Integrated Vehicle Controlmentioning

confidence: 99%

Coordinated control of multi-actuated electric vehicle

Shyrokau¹

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How the four wheels should share forces in an optimum cooperative chassis control

Cited by 103 publications

References 1 publication

Design and Analysis of DYC and Torque Vectoring using Multiple-Frequency Control Electronic Differential in an Independent Rear Wheel Driven Electric Vehicle

Design and Analysis of DYC and Torque Vectoring using Multiple-Frequency Control Electronic Differential in an Independent Rear Wheel Driven Electric Vehicle

Integrated Fault Diagnosis Algorithm for Motor Sensors of In-Wheel Independent Drive Electric Vehicles

Coordinated control of multi-actuated electric vehicle

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