A direct multiple shooting method to improve vehicle handling and stability for four hub-wheel-drive electric vehicle during regenerative braking

2019 ◽  
Vol 234 (4) ◽  
pp. 1047-1056
Author(s):  
Nenglian Feng ◽  
Jiawang Yong ◽  
Ziqi Zhan
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Shooting Method ◽  
Single Point ◽  
Function Optimization ◽  
Driver Model ◽  
Regenerative Braking ◽  
Multiple Shooting ◽  
Multiple Shooting Method ◽  
Wheel Drive

Regenerative braking is an important technology to improve fuel economy for electric vehicles. Apart from improving energy recovery efficiency and vehicle stability, the arithmetic speed of the algorithm is also essential for an automotive-qualified micro control units. This paper presents a direct multiple shooting method–based algorithm to achieve multiple objectives for four hub-wheel-drive electric vehicle during mild braking situations. Mathematical models of the system are generated for numerical simulations in MATLAB, including a vehicle dynamics model, a modified tire model, a single-point preview driver model, and a regenerative braking motor efficiency map. With the limitation of hard constraint and minimization of adjustment rate in cost function, optimization tends to be accomplished by distribution of braking torque in front and rear wheels. Furthermore, the control strategy has been realized using a direct multiple shooting method to convert the nonlinear optimal control problem to a nonlinear programming problem, which will be settled by adopting a sequential quadratic programming method in each subintervals. The effectiveness and adaptation of the control strategy for four hub-wheel-drive electric vehicle has been evaluated by conducting many simulations during mild braking situations, and the simulation results also demonstrated that the direct multiple shooting–based strategy exhibits a better performance than that of proportional-integral-based or nonlinear model predictive control–based controller.

scholarly journals Multiple shooting method in stability analysis of non-prismatic multi-segment columns

2013 ◽  
Vol 12 (4) ◽  
pp. 225-232
Author(s):  
Ryszard Hołubowski ◽  
Andrzej Merena
Keyword(s):  
Finite Element Method ◽  
Stability Analysis ◽  
Shooting Method ◽  
High Efficiency ◽  
Variable Coefficients ◽  
Multiple Shooting ◽  
System Of Differential Equations ◽  
The Finite Element Method ◽  
Concentrated Force ◽  
Multiple Shooting Method

The application of multiple shooting method in stability analysis of non-prismatic multi-segment columns with pinned ends loaded with a concentrated force applied to the upper node has been presented. Numerical analyses were carried out for an exemplary three-segment column by solving the system of differential equations with variable coefficients and parameter. The results were compared with the solution obtained by using SOFiSTiK software based on the finite element method. The analyses show that considering the stiffness changes along the length can have a significant influence on the values of critical loads and thus change the resistance of the column. The advantage of the proposed method is its high efficiency and easy description of stiffness changes.

scholarly journals Research on braking energy recovery strategy of electric vehicle based on ECE regulation and I curve

2019 ◽  
Vol 103 (1) ◽  
pp. 003685041987776 ◽  
Author(s):  
Shengqin Li ◽  
Bo Yu ◽  
Xinyuan Feng
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
State Of Charge ◽  
Regenerative Braking ◽  
Force Distribution ◽  
Battery State Of Charge ◽  
Braking Force ◽  
Braking Control ◽  
Braking Energy Recovery

Electric vehicles can convert the kinetic energy of the vehicle into electric energy for recycling. A reasonable braking force distribution strategy is the key to ensure braking stability and the energy recovery rate. For an electric vehicle, based on the ECE regulation curve and ideal braking force distribution (I curve), the braking force distribution strategy of the front and rear axles is designed to study the braking energy recovery control strategy. The fuzzy control method is adopted while the charging power limit of the battery is considered to correct the regenerative braking torque of the motor, the ratio of the regenerative braking force of the motor to the front axle braking force is designed according to different braking strengths, then the braking force distribution and braking energy recovery control strategies for regenerative braking and friction braking are developed. The simulation model of combined vehicle and energy recovery control strategy is established by Simulink and Cruise software. The braking energy recovery control strategy of this article is verified under different braking conditions and New European Driving Cycle conditions. The results show that the control strategy proposed in this article meets the requirements of braking stability. Under the condition of initial state of charge of 75%, the variation of state of charge of braking control strategy in this article is reduced by 8.22%, and the state of charge of braking strategy based on I curve reduces by 9.12%. The braking force distribution curves of the front and rear axle are in line with the braking characteristics, can effectively recover the braking energy, and improve the battery state of charge. Taking the using range of 95%–5% of battery state of charge as calculation target, the cruising range of vehicle with braking control strategy of this article increases to 136.64 km, which showed that the braking control strategy in this article could increase the cruising range of the electric vehicle.

The Improved Algorithm to Preview Follower Control Applied Research on Intelligent Electric Vehicle

2014 ◽  
Vol 1079-1080 ◽  
pp. 1022-1025
Author(s):  
Sheng Rui Liu
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Control Method ◽  
Search Algorithm ◽  
Path Model ◽  
Driver Model ◽  
Domain Modeling ◽  
Steering Control ◽  
Tracking Accuracy ◽  
Electric Cars

This paper presents an improved preview follower, electric vehicle intelligent driver model of steering control strategy. And from the preview following the model proposed steering control method, and the preview follower algorithm, propose a new preview search algorithm, in order to ensure the preview points fall within the expected path, avoid the path curvature caused by excessive electric cars from the path. In addition, by considering the steady state response, to improve the precision of steering control strategy. Use of the multi domain modeling software Dipolar, combined with the electric vehicle dynamic model, the path model of the steering control strategy simulation. The simulation results show that the strategy is applied to electric vehicle path goal good tracking accuracy.

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