Junzhi Zhang

Cooperative control of regenerative braking and hydraulic braking of an electrified passenger car

With the aims of regeneration efficiency and brake comfort, three different control strategies, namely the maximum-regeneration-efficiency strategy, the good-pedal-feel strategy and the coordination strategy for regenerative braking of an electrified passenger car are researched in this paper. The models of the main components related to the regenerative brake and the frictional blending brake of the electric passenger car are built in MATLAB/Simulink. The control effects and regeneration efficiencies of the control strategies in a typical deceleration process are simulated and analysed. Road tests under normal deceleration braking and an ECE driving cycle are carried out. The simulation and road test results show that the maximum-regeneration-efficiency strategy, which causes issues on brake comfort and safety, could hardly be utilized in the regenerative braking system adopted. The good-pedal-feel strategy and coordination strategy are advantageous over the first strategy with respect to the brake comfort and regeneration efficiency. The fuel economy enhanced by the regenerative braking system developed is more than 25% under the ECE driving cycle.

Extended-Kalman-filter-based regenerative and friction blended braking control for electric vehicle equipped with axle motor considering damping and elastic properties of electric powertrain

Because of the damping and elastic properties of an electrified powertrain, the regenerative brake of an electric vehicle (EV) is very different from a conventional friction brake with respect to the system dynamics. The flexibility of an electric drivetrain would have a negative effect on the blended brake control performance. In this study, models of the powertrain system of an electric car equipped with an axle motor are developed. Based on these models, the transfer characteristics of the motor torque in the driveline and its effect on blended braking control performance are analysed. To further enhance a vehicles brake performance and energy efficiency, blended braking control algorithms with compensation for the powertrain flexibility are proposed using an extended Kalman filter. These algorithms are simulated under normal deceleration braking. The results show that the brake performance and blended braking control accuracy of the vehicle are significantly enhanced by the newly proposed algorithms.

Integrated control of braking energy regeneration and pneumatic anti-lock braking

Abstract This paper mainly focuses on integrated control of the brake system of a hybrid electric vehicle, i.e. the integration of friction braking and regenerative braking during anti-lock braking control and series brake blending during normal deceleration. Based on a series regenerative braking system, the structure of an integrated brake system is proposed. The models of each part of a hybrid electric bus are built in MATLABÆ Simulink, taking authorized articles as references. A test bench with the original pneumatic brake system of a bus is also built to carry out hardware-in-the-loop (HIL) tests of the integrated brake system and to study the characteristics of the system better. The integrated control strategy is proposed on the basis of a pneumatic anti-lock braking strategy. Simulation results show that the participation of regenerative braking in the anti-lock braking control can be beneficial to both the ride comfort and the braking performance of the vehicle. HIL test results validate the results of the simulations. An integrated brake controller is designed and made to carry out the control strategies on board. A field in which further research could be carried out is also proposed.

Hardware-in-the-loop simulation of pressure-difference-limiting modulation of the hydraulic brake for regenerative braking control of electric vehicles

Because of its significant impact on the cooperative regenerative braking performance of electrified vehicles, the modulation effect of a hydraulic brake is of great importance. To improve the hydraulic brake control performance further, a novel pressure-difference-limiting control method for hydraulic pressure modulation based on on–off solenoid valves is proposed. The linear relationship between the coil current and the pressure difference across the valve is obtained. The characteristics of pressure-difference-limiting modulation are simulated and analysed. Then, a cooperative regenerative braking control algorithm based on the pressure-difference-limiting modulation of the hydraulic brake is designed. Hardware-in-the-loop tests of the algorithm under typical braking procedures are carried out. The test results demonstrate the validity and feasibility of the developed regenerative braking control algorithm and indicate that the proposed pressure-difference-limiting modulation method, which has an advantage over the conventional control based on a pulse-width-modulated signal with respect to the control accuracy of the hydraulic brake pressure, has great potential to improve the braking performance of a vehicle.

Study on a linear relationship between limited pressure difference and coil current of on/off valve and its influential factors

On/off solenoid valves with PWM control are widely used in all types of vehicle electro-hydraulic control systems respecting to their desirable properties of reliable, low cost and fast acting. However, it can hardly achieve a linear hydraulic modulation by using on/off valves mainly due to the nonlinear behaviors of valve dynamics and fluid, which affects the control accuracy significantly. In this paper, a linear relationship between limited pressure difference and coil current of an on/off valve in its critical closed state is proposed and illustrated, which has a great potential to be applied to improve hydraulic control performance. The hydraulic braking system of case study is modeled. The linear correspondence between limited pressure difference and coil current of the inlet valve is simulated and further verified experimentally. Based on validated simulation models, the impacts of key parameters are researched. The limited pressure difference affected by environmental temperatures is experimentally studied, and the amended linear relation is given according to the test data.

Mode-Switching-Based Active Control of a Powertrain System with Non-Linear Backlash and Flexibility for an Electric Vehicle during Regenerative Deceleration

Regenerative braking provided by an electric powertrain is very different from conventional friction braking with respect to the system dynamics. During regenerative decelerations, the powertrain backlash and flexibility excite driveline oscillations, causing the vehicle driveability and the blended brake performance to deteriorate. In this article, system models, including a powertrain model with non-linear backlash and flexibility, and a hydraulic brake system model, are developed. The effects of the powertrain backlash and the flexibility on the vehicle driveability during regenerative deceleration are analysed. To improve the driveability and the blended braking performance of an electric vehicle further, a mode-switching-based active control algorithm with a hierarchical architecture is developed providing compensation for the backlash and the flexibility. The proposed control algorithms are simulated and compared with the baseline strategy under the regeneration braking process. The simulation results show that the vehicle driveability and the blended braking performance can be significantly enhanced by the developed active control algorithm.

Levenberg–Marquardt Backpropagation Training of Multilayer Neural Networks for State Estimation of a Safety-Critical Cyber-Physical System

As an important safety-critical cyber-physical system (CPS), the braking system is essential to the safe operation of the electric vehicle. Accurate estimation of the brake pressure is of great importance for automotive CPS design and control. In this paper, a novel probabilistic estimation method of brake pressure is developed for electrified vehicles based on multilayer artificial neural networks (ANNs) with Levenberg–Marquardt backpropagation (LMBP) training algorithm. First, the high-level architecture of the proposed multilayer ANN for brake pressure estimation is illustrated. Then, the standard backpropagation (BP) algorithm used for training of the feed-forward neural network (FFNN) is introduced. Based on the basic concept of BP, a more efficient training algorithm of LMBP method is proposed. Next, real vehicle testing is carried out on a chassis dynamometer under standard driving cycles. Experimental data of the vehicle and the powertrain systems are collected, and feature vectors for FFNN training collection are selected. Finally, the developed multilayer ANN is trained using the measured vehicle data, and the performance of the brake pressure estimation is evaluated and compared with other available learning methods. Experimental results validate the feasibility and accuracy of the proposed ANN-based method for braking pressure estimation under real deceleration scenarios.

Modeling and analysis of regenerative braking system for electric vehicle based on AMESim

This paper presents a parametric and modularized method in modeling the hydraulic components of the regenerative braking system, through which the newly built model has gained noticeable improvement in precision. The strategy for the exiting of the regenerative braking is optimized. The simulations are conducted in the co-simulation platform between AMESim and MATLAB/Simulink at the initial vehicle speed of 40 Km/h. The simulation results show that the newly built hydraulic model can describe the process of pressure increase and decrease precisely. Meanwhile the motor cooperates with the hydraulic braking system well throughout the whole braking procedure. The maximum jerk exerted on the vehicle is decreased from 2.69 m/s3 to 0.59 m/s3 during the exiting of regenerative braking, and the regeneration efficiency is increased to 76.18%.

Research on control strategy of electric-hydraulic hybrid anti-lock braking system of an electric passenger car

Equipped with the regenerative braking system, electric vehicle coordinates friction braking and regenerative braking appropriately in normal braking conditions and activates anti-lock braking system (ABS) in emergency braking conditions. This paper mainly focuses on the control strategy of electric-hydraulic blended brake for ABS control of an electric passenger car. According to the variation of the adhesion coefficient under different roads, the maximum adhesion force and the optimal slip ratio are calculated in real-time. Then, the control strategy of electric-hydraulic hybrid ABS, in which regenerative braking and hydraulic braking are coordinated in order to obtain the maximum available road adhesion and guarantee vehicles braking stability, is proposed. Based on the control strategy developed, simulations and test-bench experiments are carried out. Simulation and test results indicate that braking stability and control performance of vehicle on different roads are guaranteed by the proposed hybrid ABS control, validating the feasibility and the effectiveness of the algorithms. Compared with conventional hydraulic ABS, the electric-hydraulic hybrid ABS, ensuring better braking performance on various road surfaces, provides a good solution to active safety control of EVs.

Research of parameter design and matching of powertrain system in plug-in hybrid electric vehicle

The characteristic and classification of plug-in hybrid electrical vehicle introduced firstly. Then, a method for design and matching of PHEV and control strategy is introduced, an example of design and matching PHEV is given. Finally, simulate the PHEV model in different working conditions based on Advisor, comparing the simulation results with the protype vehicle, analyzing and illustrating some relevant problems involved and give suggestions.