Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization

Lin, Cheng; Xu, Zhijie

doi:10.3390/en8053815

Cited by 69 publications

(40 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, (F C /z 1 ) ∈ [2.1, 3.9] and (I R /z 2 ) ∈ [2.4, 5.2] are the intervals. In general, the penalty factor M should be appropriately chosen: If it is too small, the minimal point of the penalty function is apart from the optimal solution and results in a low efficiency; if it is too large, the penalty function minimization would be very slow [41]. Since C V is large enough compared to that of the normalized fuel costs and risk index, M is chosen to be 1.…”

Section: Design Of Reward Functionmentioning

confidence: 99%

Bacteria Foraging Reinforcement Learning for Risk-Based Economic Dispatch via Knowledge Transfer

et al. 2017

View full text Add to dashboard Cite

This paper proposes a novel bacteria foraging reinforcement learning with knowledge transfer method for risk-based economic dispatch, in which the economic dispatch is integrated with risk assessment theory to represent the uncertainties of active power demand and contingencies during power system operations. Moreover, a multi-agent collaboration is employed to accelerate the convergence of knowledge matrix, which is decomposed into several lower dimension sub-matrices via a knowledge extension, thus the curse of dimension can be effectively avoided. Besides, the convergence rate of bacteria foraging reinforcement learning is increased dramatically through a knowledge transfer after obtaining the optimal knowledge matrices of source tasks in pre-learning. The performance of bacteria foraging reinforcement learning has been thoroughly evaluated on IEEE RTS-79 system. Simulation results demonstrate that it can outperform conventional artificial intelligence algorithms in terms of global convergence and convergence rate.

show abstract

Section: Design Of Reward Functionmentioning

confidence: 99%

Bacteria Foraging Reinforcement Learning for Risk-Based Economic Dispatch via Knowledge Transfer

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Even though variable torque distribution of the distributed‐drive EV was discussed for multiobjective coordination, multiobjective optimization for integrated vehicle dynamics management of the distributed‐drive EV with AFS is still a new research area in EV technology. As shown in Figure , an integrated vehicle dynamics management method of the distributed‐drive EV with AFS is studied in this paper to coordinate the commands for vehicle lateral dynamics, longitudinal dynamics, and energy saving control from the top to lower layer to regulate the steering system, traction system, and braking system.…”

Section: Introductionmentioning

confidence: 99%

Integrated vehicle dynamics management for distributed‐drive electric vehicles with active front steering using adaptive neural approaches against unknown nonlinearity

Huang

Wong

2019

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

Summary This paper proposes a new integrated vehicle dynamics management for enhancing the yaw stability and wheel slip regulation of the distributed‐drive electric vehicle with active front steering. To cope with the unknown nonlinear tire dynamics with uncertain disturbances in integrated control problem of vehicle dynamics, a neuro‐adaptive predictive control is therefore proposed for multiobjective coordination of constrained systems with unknown nonlinearity. Unknown nonlinearity with unmodeled dynamics is modeled using a random projection neural network via adaptive machine learning, where a new adaptation law is designed in premise of Lyapunov stability. Given the computational efficiency, a neurodynamic method is extended to solve the constrained programming problem with unknown nonlinearity. To test the performance of the proposed control method, simulations were conducted using a validated vehicle model. Simulation results show that the proposed neuro‐adaptive predictive controller outperforms the classical model predictive controller in tracking nominal wheel slip ratio, desired vehicle yaw rate and sideslip angle, showing its significance in vehicle yaw stability enhancement and wheels slip regulation.

show abstract

“…Most general designs consist of two pairs of gearsets in different speed ratios, and utilize clutches, brakes, or motors to control the direction of the transferred wheel torque [10][11][12][13][14]. However, the two pairs of gearsets or motors in current designs result in heavier system weight and larger space requirements.…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of a New Torque Vectoring System with a Ravigneaux Gearset for Vehicle Applications

Chen

Chang

et al. 2017

Energies

View full text Add to dashboard Cite

Abstract:The purpose of this research is to develop a new torque vectoring differential (TVD) for vehicle applications and investigate its effect on vehicle dynamic control. TVD is a technology that is able to distribute the engine torque to the left and right driving wheels at different ratios so that the yaw motion control can be realized. Attention has been paid to this technology in recent years because of its potential to improve the vehicle performance and driving safety. In this study, a new TVD design with a Ravigneaux gearset was developed. This new design is able to use only one pair of gearsets to generate two different speed ratios, and the weight and volume of the system can be reduced. To execute the research, current TVD designs were analyzed and their design principles were clarified. Next, a new TVD design with Ravigneaux gearset was proposed. Then the connecting manner and the gear ratio of the Ravigneaux gearset were discussed. The dynamic equation of the system was then derived and the operation of the system was simulated in a MATLAB program. Further simulation was performed with a vehicle dynamic model in SimulationX to demonstrate the effect of the new system. The results of this study show the potential of building a new TVD with a Ravigneaux gearset and can be helpful for further system development.

show abstract

Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization

Cited by 69 publications

References 17 publications

Bacteria Foraging Reinforcement Learning for Risk-Based Economic Dispatch via Knowledge Transfer

Bacteria Foraging Reinforcement Learning for Risk-Based Economic Dispatch via Knowledge Transfer

Integrated vehicle dynamics management for distributed‐drive electric vehicles with active front steering using adaptive neural approaches against unknown nonlinearity

Design and Analysis of a New Torque Vectoring System with a Ravigneaux Gearset for Vehicle Applications

Contact Info

Product

Resources

About