2014
DOI: 10.3390/en7074614
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Abstract: Abstract:Vehicle active safety control is attracting ever increasing attention in the attempt to improve the stability and the maneuverability of electric vehicles. In this paper, a neural network combined inverse (NNCI) controller is proposed, incorporating the merits of left-inversion and right-inversion. As the left-inversion soft-sensor can estimate the sideslip angle, while the right-inversion is utilized to decouple control. Then, the proposed NNCI controller not only linearizes and decouples the origina… Show more

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Cited by 9 publications
(7 citation statements)
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“…between 0.1 and 0.3 for the slip ratio. 11 In the slip-ratio-based anti-skid controller, if an excessive torque is applied on the driving wheels under slippery road conditions, a quick increase in the slip ratio easily causes the friction coefficient to enter the unstable region, where the sudden loss in the traction force due to the decrease in the friction coefficient may cause the vehicle to skid. Furthermore, the behaviour of the vehicle in the unstable region of the friction coefficient curve can be very difficult to control.…”
Section: Conventional Slip-ratio-based Anti-skid Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…between 0.1 and 0.3 for the slip ratio. 11 In the slip-ratio-based anti-skid controller, if an excessive torque is applied on the driving wheels under slippery road conditions, a quick increase in the slip ratio easily causes the friction coefficient to enter the unstable region, where the sudden loss in the traction force due to the decrease in the friction coefficient may cause the vehicle to skid. Furthermore, the behaviour of the vehicle in the unstable region of the friction coefficient curve can be very difficult to control.…”
Section: Conventional Slip-ratio-based Anti-skid Methodsmentioning
confidence: 99%
“…easy-to-implement distributed in-wheel motor systems (electric motors usually have compact sizes but powerful and flexible outputs, which can improve the dynamic control stability 4,912 and the energy efficiency 13 and which are fun to drive 14 ).…”
Section: Introductionmentioning
confidence: 99%
“…Artificial neural networks have been employed to develop soft sensors for many industrial processes to control unmeasurable variables [22][23][24][25][26]. Although such soft sensors can exhibit high fitting precision on the test data sets, they cannot explain process mechanisms, and hence can lack of robustness in the presence of process uncertainty.…”
Section: Formulation Of the Soft Sensormentioning
confidence: 99%
“…The distinct advantages of well-controlled electric motors may include fast torque response [1,3], simple dynamics [1,4], easy-to-obtain torque feedback (the torque generated from electric motors is proportional to the motor current for industrial applications [5,6]), capability of generating both traction and braking forces (regenerative braking during deceleration can be realized using electric motors [7,8]), and easy-to-implement distributed in-wheel motor systems (electric motors usually have compact sizes but powerful and flexible outputs, which can improve dynamic control stability [4,9,10], energy efficiency [11], and fun to drive [12]). …”
Section: Introductionmentioning
confidence: 99%