Mode-switch model predictive controller with “pre-contact” method for alleviating driveline vibration of electric vehicles considering backlash

Author(s):  
Xingyang Lu ◽  
Tongli Lu ◽  
Benben Chai

The backlash between engaging components in a driveline is inevitable and contributes to the nonlinearity of the driveline. The existing motor controllers of an electric vehicle usually ignore the backlash, which often brings impacts and vibration. This paper proposes an active driveline vibration controller for electric vehicles. A nonlinear driveline model considering backlash and wheel slip ratio is established in MATLAB/Simulink, and the results of bench test proved that the model could effectively reflect the transient dynamics of the electric driveline. Based on this model, a dual extended Kalman filter observer is designed to estimate both the system state variables and vehicle mass, which are essential information for the controller design. Then, a mode-switch model predictive controller based on two linearized models is proposed to alleviate the impacts and vibration caused by the transient change of motor torque. The proposed controller would identify whether the driveline is operating in “contact mode” or “backlash mode” and thus generates an optimal motor torque by solving a Quadratic Programing. Note that the control targets and model structures in two modes are different. Furthermore, a “pre-contact” method is proposed as an additional part to handle the condition when motor command torque is zero. Simulation results demonstrate that the proposed controller can effectively alleviate the impacts and vibration in the electric driveline while keeping the torque delay negligible. Moreover, the robustness of the proposed controller against estimation errors and system noises are discussed.

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Y. Bello ◽  
T. Azib ◽  
C. Larouci ◽  
M. Boukhnifer ◽  
N. Rizoug ◽  
...  

The eco-driving profiles are algorithms able to use additional information in order to create recommendations or limitation over the driver capabilities. They increase the autonomy of the vehicle but currently their usage is not related to the autonomy required by the driver. For this reason, in this paper, the eco-driving challenge is translated into two-layer optimal controller designed for pure electric vehicles. This controller is oriented to ensure that the energy available is enough to complete a demanded trip, adding speed limits to control the energy consumption rate. The mechanical and electrical models required are exposed and analyzed. The cost function is optimized to correspond to the needs of each trip according to driver behavior, vehicle, and traject information. The optimal controller proposed in this paper is a nonlinear model predictive controller (NMPC) associated with a nonlinear unidimensional optimization. The combination of both algorithms allows increasing around 50% the autonomy with a limitation of the 30% of the speed and acceleration capabilities. Also, the algorithm is able to ensure a final autonomy with a 1.25% of error in the presence of sensor and actuator noise.


2020 ◽  
Vol 69 (5) ◽  
pp. 4935-4946 ◽  
Author(s):  
Ningyuan Guo ◽  
Basilio Lenzo ◽  
Xudong Zhang ◽  
Yuan Zou ◽  
Ruiqing Zhai ◽  
...  

Author(s):  
Fatemeh Khani ◽  
Mohammad Haeri

Industrial processes are inherently nonlinear with input, state, and output constraints. A proper control system should handle these challenging control problems over a large operating region. The robust model predictive controller (RMPC) could be an linear matrix inequality (LMI)-based method that estimates stability region of the closed-loop system as an ellipsoid. This presentation, however, restricts confident application of the controller on systems with large operating regions. In this paper, a dual-mode control strategy is employed to enlarge the stability region in first place and then, trajectory reversing method (TRM) is employed to approximate the stability region more accurately. Finally, the effectiveness of the proposed scheme is illustrated on a continuous stirred tank reactor (CSTR) process.


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