Regenerative brake control strategy based on electro-hydraulic brake system

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.

Through the analysis of the regenerative braking system of pure electric vehicles, a series type of regenerative braking control strategy based on a full decoupling braking system is proposed from the perspective of vehicle braking dynamics. The main factors influencing the regenerative braking control of pure electric vehicles are analyzed. Based on this, several common braking control strategies of regenerative systems are elaborated and analyzed according to the main influencing factors. Through the comparative analysis of the braking control strategies of the regenerative system, it is found that the parallel linkage brake control strategy can better meet the safe operation of pure electric vehicles. Compared with the original control strategy, the regenerative braking combined control strategy can improve the energy recovery rate when the vehicle is braking at high braking intensity and it can also improve the failure safety of the electronic control system when the vehicle is braking at high speed or at medium and high intensity.

To enhance the efficiency of braking energy recovery in distributed electric vehicles, this study investigates the impact of vehicle velocity prediction on braking performance. A regenerative braking control strategy that incorporates vehicle velocity prediction is proposed. Initially, a vehicle velocity prediction model is developed using a backpropagation neural network, which is trained under various operational conditions, and its validity is confirmed through testing. Subsequently, a braking control strategy that integrates vehicle velocity prediction is formulated based on a parallel braking control approach to optimize braking energy recovery. Finally, simulations of the proposed control strategy are conducted and compared with a strategy that does not utilize velocity prediction, under both joint working conditions and the Worldwide Harmonized Light Vehicles Test Cycle (WLTC). The findings indicate that the control strategy utilizing vehicle velocity prediction achieves greater energy recovery in both scenarios, with improvements in braking energy recovery efficiency of 9.2% and 6.13% over the non-predictive strategy, respectively. These results demonstrate the efficacy and rationale of the proposed approach.

Nowadays, regenerative braking is one of the most prevalent and important technology applied in EV (electric vehicle). It can extend the driving range of EV by transforming part of kinetic energy into electric energy during the braking process of EV. The research object of this paper is one certain EV with the hybrid electric power which includes lithium ion battery and ultra-capacitor. This paper establishes the circuit mathematical model of RBS (regenerative braking system) and analyzes the system comprehensively. Based on that, this paper designs a braking force distribution method between the front-axle and rear-axle. Under the premise of braking safety, this paper puts forward a variable current regenerative braking control strategy based on RBF (radial basis function) neural network tuning PID control with the aim of maximum energy recovery. In order to prove the validity of the model and the control strategy, this paper contrasts the variable current regenerative braking control strategy with the traditional constant current braking control strategy by bench test and simulation under NEDC driving cycle. The result shows that the variable current regenerative braking control strategy is effective, improving the energy recovery efficiency, extending the driving range of EV.

Due to the introduction of multiple subsystems, it is very difficult for a hydraulic hybrid loader to improve its fuel economy with traditional braking control strategy and classic optimization algorithm. To deal with this problem, a combined braking control strategy based on fuzzy control system was proposed. In this strategy, the current working step and working cycle were first recognized with sensor signals. And the optimal control rules for different working cycles were optimized by genetic algorithm off line. After doing that, the obtained control rules were used to control the braking process and the energy distribution process of loaders. Simulation and experimental results show that the control strategy can make full use of the braking energy and can improve the recovery rate of it under the guarantee of safety and stability.

To explore the brake control strategy more suitable for heavy-duty multi-axle special vehicles, a comparative analysis of anti-lock brake system (ABS) control strategies based on heavy multi-axle special vehicles was carried out. Use Matlab/Simulink to build a heavy-duty single-wheel anti-lock control system including dynamics model, slip rate model, tire model, braking model and controller model. The current main control strategies are adopted: no ABS, logic Threshold control, PID control, sliding mode variable structure control, fuzzy PID control and nonlinear active disturbance rejection control are simulated and compared.The research results show that: (1) The comparison of anti-lock braking control strategies for heavy-duty multi-axle special vehicles can be achieved simply and quickly through Matlab/Simulink heavy-duty single-wheel parametric model simulation; (2) Several control strategies have obvious advantages and disadvantages , Needs to be selected according to actual needs; (3) Comprehensive control strategy characteristics and special vehicle requirements, nonlinear auto disturbance rejection control is more suitable for heavy-duty multi-axle special vehicle braking control.

With the rapid advancements in autonomous driving and intelligent braking technologies, there has been a corresponding evolution in the pneumatic braking systems of commercial vehicles. This evolution is pivotal for enabling the integration of more active safety strategies into Commercial Vehicle Electronic Controlled Pneumatic Braking Systems (ECPBS). This paper introduces an innovative ECPBS design for commercial vehicles, centered around an automatic pressure regulating valve. It delves into a comprehensive analysis of the working principles and braking control strategies, incorporating an integrated approach of hardware and software design, simulation modeling, and experimental validation. A sophisticated Hardware-in-the-Loop (HIL) validation system has been developed for the entire vehicle’s braking control strategy in the commercial vehicle ECPBS. Utilizing specific application scenarios, this system underwent HIL testing experiments to validate the ECPBS, based on the automatic pressure regulating valve. The results from these validation tests affirm that the ECPBS possesses both fundamental braking capabilities and the aptitude for implementing advanced braking control strategies. This study provides crucial technical support for the development and broader implementation of autonomous driving and intelligent braking technologies in commercial vehicles, particularly in the context of new system architectures.

Most parallel hybrid electric vehicles (HEV) employ both a hydraulic braking system and a regenerative braking system to provide enhanced braking performance and energy regeneration. A new design of a combined braking control strategy (CBCS) is presented in this paper. The design is based on a new method of HEV braking torque distribution that makes the hydraulic braking system work together with the regenerative braking system. The control system meets the requirements of a vehicle longitudinal braking performance and gets more regenerative energy charge back to the battery. In the described system, a logic threshold control strategy (LTCS) is developed to adjust the hydraulic braking torque dynamically, and a fuzzy logic control strategy (FCS) is applied to adjust the regenerative braking torque dynamically. With the control strategy, the hydraulic braking system and the regenerative braking system work synchronously to assure high regenerative efficiency and good braking performance, even on roads with a low adhesion coefficient when emergency braking is required. The proposed braking control strategy is steady and effective, as demonstrated by the experiment and the simulation.

The characteristics of electro-hydraulic braking systems have a direct influence on the fuel consumption, emissions, brake safety, and ride comfort of hybrid electric vehicles. In order to realize efficient energy recovery for ensuring braking safety and considering that the existing electro-hydraulic braking pressure control systems have control complexity disadvantages and functional limitations, this study considers the front and rear dual-motor-driven hybrid electric vehicle as the prototype and based on antilock brake system (ABS) hardware, proposes a new braking pressure coordinated control system with electro-hydraulic braking function and developed a corresponding control strategy in order to realize efficient energy recovery and ensure braking safety, while considering the disadvantages of control complexity and functional limitations of existing electro-hydraulic system. The system satisfies the pressure coordinated control requirements of conventional braking, regenerative braking, and ABS braking. The vehicle dynamics model based on braking control strategy and pressure coordinated control system is established, and thereafter, the performance simulation of the vehicle-based pressure coordinated control system under typical braking conditions is carried out to validate the performance of the proposed system and control strategy. The simulation results show that the braking energy recovery rates under three different conditions—variable braking intensity, constant braking intensity and integrated braking model—are 66%, 55% and 47%. The battery state of charge (SOC) recovery rates are 0.37%, 0.31% and 0.36%. This proves that the motor can recover the reduced energy of the vehicle during braking and provide an appropriate braking force. It realizes the ABS control function and has good dynamic response and braking pressure control accuracy. The simulation results illustrate the effectiveness and feasibility of the program which lays the foundation for further design and optimization of the new regenerative braking system.

<div class="htmlview paragraph">The problem of vehicle stability in emergency maneuvers has attracted a lot of research effort recently. Perhaps the most effective contributions made in this area were devoted to the control of vehicle yaw rate either by active steering or differential braking control systems. Each control technique has its own limitations that make it ineffective in some particular situations. This paper introduces a combined steering and braking control strategy using a fuzzy logic inference system. The proposed controller uses the estimated coefficient of friction (μ) to organize the combined control action. Computer simulation using a comprehensive vehicle model is used to illustrate the strengths and limitations of various control strategies.</div>

Aiming at the emergency braking and rapid response of the Unmanned Aerial Vehicle (UAV) operating on the ground, a novel brake control strategy is proposed in this paper, adopting an integrated design of pressure and velocity based on sliding mode control. The strategy takes the air travel in the operation of the all-electric brake system into consideration. In this paper, the controller of an UAV Hardware-in-the-Loop (HIL) test system will be used to verify the feasibility of the novel brake control strategy and the simulation results are adopted to validate the superiority and feasibility of the brake control strategy for UAV all-electric brake system.

Parametric design and regenerative braking control of a parallel hydraulic hybrid vehicle

Theoretical study on energy recovery rate of regenerative braking for hybrid mining trucks with different parameters

Electric wheel-drive multi-axle heavy-duty vehicles have the characteristics of strong maneuverability and good passability, thereby they are widely used in heavy equipment transportation. However, current research on the composite braking of multi-axle heavy-duty vehicles is rare, which is not conducive to improving braking performance and braking energy utilization efficiency. This work proposes a multi-mode composite braking control strategy for the five-axle distributed electric wheel-drive heavy-duty vehicle. Firstly, given the differences in braking dynamics between two-axle vehicles and multi-axle vehicles, the brake dynamics characteristics of multi-axle vehicles are analyzed, and the vehicle dynamics model of multi-axle vehicles is constructed. Next, a multi-mode composite braking control strategy including a fully electric braking state and hybrid electro–hydraulic braking state is proposed in order to improve the braking energy recovery and braking stability. Finally, a hardware-in-the-loop simulation system is established, and the single-braking conditions and China heavy-duty commercial vehicle test cycle-heavy truck (abbreviated as CHTC-HT) are conducted to verify the performance of the braking control strategy. The results indicate that the recaptured braking energy and braking stability are significantly increased by applying the control strategy proposed in this work.

This paper, based on the performance characteristics of electric vehicles, provides a rather integrated set of control strategies of sensor-less brushless DC motor for electric vehicles. It probes into the key technical issues of sensor-less brushless DC motor control - the rotor position detection, starting and braking control strategies, accelerating demagnetization method and the speed-current double-loop speed control. Also, it improves the control methods on the basis of some traditional ones to make it more suitable for electric vehicles which require high-speed, steadiness and power-saving, meanwhile introduces the improved hysteresis current control to perfect the motor performance characteristics. The emulation results show that this control algorithm can meet the work requirements of electric vehicles while the motor working under expected state.