Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer

Geng, C.; Mostefai, L.; Denaï, Mouloud; Hori, Yoichi

doi:10.1109/tie.2009.2013737

Cited by 249 publications

(20 citation statements)

References 19 publications

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“…Sensor sets including individual sensors are the least favorable configurations based on the measures in Equations (27), (28), (29), (30), (31), (32), (33). However, the system is observable with all the introduced sensor sets, assuming the model (1), (2), (3), (4), (5), (6), (7), (8), (9), (10), (11), (12), (13), (14), (15), (16), (17), (18) …”

Section: Table 1 Results Of the Observability Analysismentioning

confidence: 99%

“…This model represents handling dynamics of the vehicle and includes lateral acceleration (a y ), yaw rate (r) and roll rate ( ) as dominant elements that contribute to the handling performance. The majority of studies that focused on vehicle handling dynamics consider a 2-DOF vehicle model that only includes yaw and lateral motions [13], [14], [15]. However, the roll motion can significantly affect the handling dynamics due to lateral load transfer.…”

Section: Vehicle Modelmentioning

confidence: 99%

“…For the 3-DOF vehicle model described by Equations (1), (2), (3), (4), (5), (6), (7), (8), (9), (10), (11), (12), (13), (14), (15), (16), (17), (18) The results verify the desirable performance of the estimator despite modeling uncertainties and simplicity of the model.…”

Section: Estimation Of Vehicle Statesmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Sensor Configuration and Fault-Tolerant Estimation of Vehicle States

Zarringhalam

Rezaeian

Fallah

et al. 2013

SAE Int. J. Passeng. Cars – Electron. Electr. Syst.

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This paper discusses observability of the vehicle states using different sensor configurations as well as fault-tolerant estimation of these states. The optimality of the sensor configurations is assessed through different observability measures and by using a 3-DOF linear vehicle model that incorporates yaw, roll and lateral motions of the vehicle. The most optimal sensor configuration is adopted and an observer is designed to estimate the states of the vehicle handling dynamics. Robustness of the observer against sensor failure is investigated. A fault-tolerant adaptive estimation algorithm is developed to mitigate any possible faults arising from the sensor failures. Effectiveness of the proposed fault-tolerant estimation scheme is demonstrated through numerical analysis and CarSim simulation.

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Section: Table 1 Results Of the Observability Analysismentioning

confidence: 99%

Section: Vehicle Modelmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Sensor Configuration and Fault-Tolerant Estimation of Vehicle States

Zarringhalam

Rezaeian

Fallah

et al. 2013

SAE Int. J. Passeng. Cars – Electron. Electr. Syst.

View full text Add to dashboard Cite

show abstract

“…In some references [12], [13], [14] this module has been defined as upper-controller which its function is to generate the desired signals so as to keep the vehicle in stable regions. However, this concept may result in over-restricting the driver in emergency cases.…”

Section: Driver Command Interpretermentioning

confidence: 99%

“…Based upon the tire/road conditions, it is required to define an upper-bound on desired forces calculated in (11), (12), (13) in order to avoid generating excessive side and longitudinal slips. In steady state and stable conditions without side-slip, the upper-bound are defined as follows:…”

Section: (24)mentioning

confidence: 99%

Optimal Torque Control for an Electric-Drive Vehicle with In-Wheel Motors: Implementation and Experiments

Athari¹,

Fallah²,

Li³

et al. 2013

SAE Int. J. Commer. Veh.

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This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the interpreter command. A test vehicle equipped with four in-wheel electric motors, vehicle sensors, communication buses, and dSPACE rapid prototyping hardware is instrumented and the control performance is verified through vehicle handling tests under different driving conditions.

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GPS Based Estimation of Vehicle Sideslip Angle Using Multi-Rate Kalman Filter with Prediction of Course Angle Measurement Residual

Nguyen

Wang

et al. 2012

Lecture Notes in Electrical Engineering

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Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer

Cited by 249 publications

References 19 publications

Optimal Sensor Configuration and Fault-Tolerant Estimation of Vehicle States

Optimal Sensor Configuration and Fault-Tolerant Estimation of Vehicle States

Optimal Torque Control for an Electric-Drive Vehicle with In-Wheel Motors: Implementation and Experiments

GPS Based Estimation of Vehicle Sideslip Angle Using Multi-Rate Kalman Filter with Prediction of Course Angle Measurement Residual

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