Braking Recovery Research Articles

Study of a horizontal seat suspension with a model of the seated human body and energy recovery braking subsystem

Study of a horizontal seat suspension with a model of the seated human body and energy recovery braking subsystem

Recovery and Control Strategy of Electro-Hydraulic Composite Braking Energy for Electric Loader with Braking Intention Recognition

The loader has a lot of recoverable braking energy due to its larger mass and frequent starts/stops. For a 5-ton pure electric drive loader, an emergency braking intention recognition strategy based on hydraulic braking pressure was proposed. The braking intention recognition strategy of an acceleration pedal and brake pedal was used to distinguish different braking intentions, and the hydraulic braking system pressure was used as a feedback parameter for emergency braking intention recognition to improve braking safety. Aiming at electro-hydraulic composite braking mode switching, a collaborative control strategy of walking regenerative braking and mechanical braking is proposed. Simulation analysis by AMESim and vehicle test results show that the proposed control strategy can realize driver braking intention recognition and electro-hydraulic braking force distribution under different working conditions and improve braking smoothness. According to the calculation of the energy recovery effect evaluation index, the energy recovery efficiency is up to 71.64%, the braking recovery rate is above 42.50%, and the maximum energy saving for the whole vehicle is 7.58% under one cycle condition. The proposed strategy has a good energy-saving effect.

Data-driven analysis of battery electric vehicle energy consumption under real-world temperature conditions

Demand for battery electric vehicles has grown significantly in recent years as global oil prices have climbed. The current development of battery electric vehicles is still in its infancy, and its energy consumption also requires great attention. Five same model battery electric vehicles' driving condition data of a certain brand in Tianjin area are collected for a whole year, and their energy consumption is analyzed. The results show that the energy consumption of the actual driving conditions in the four seasons is generally higher than the test results under New European Driving Cycle, and only some vehicles' energy consumption in spring and autumn is consistent with the test results under Worldwide Harmonized Light Vehicles Test Cycle. Energy consumption tends to increase at both ends with the change of temperature. The impact of low temperature is greater, because the air conditioner usage rate and power in Winter are higher than those in Summer. Through principal component contribution rate analysis and K-means clustering calculation of micro-trips, the results show that the average energy consumption in urban, suburban and high-speed driving conditions decreases gradually. Driving habits such as rapid acceleration ratio and rapid deceleration ratio also have an impact on energy consumption. The decrease of energy braking recovery indirectly caused by rapid deceleration ratio increase makes the energy consumption per 100 km increase. And the increase of rapid acceleration ratio leads to an increase in energy consumption per 100 km. Finally, the Spearman rank correlation analysis shows that energy consumption has the greatest correlation with the average vehicle speed and air conditioner usage status, followed by the constant speed proportion, idle speed proportion and temperature, and finally the recovery of braking energy per 100 km, acceleration proportion, deceleration proportion and rapid acceleration proportion.

DQN regenerative braking control strategy based on adaptive weight coefficients

Aiming at the problems existing in regenerative braking control strategy based on Q-learning which include the dimensional disaster of state and action variables discretization and the return function weight coefficient determined empirically. This paper proposes deep Q-learning network (DQN) regenerative braking control strategy based on adaptive weight coefficients. Firstly, braking performance evaluation indexes are determined which are braking energy recovery efficiency and braking stability coefficient. Then, the state and action variables and return function are constructed respectively. Therein the braking demand power and state of charge ( SOC) are taken as state variables, braking torque proportional coefficient, and weight coefficients are taken as action variables. And return function is formulated by trading off braking energy recovery efficiency and braking stability. Finally, using the MATLAB/Simulink software, the simulation model of real working condition in Yubei district of Chongqing is established. The simulation results show that braking recovery efficiency of the proposed strategy is 7.4% higher than that of Q-learning strategy, and the average braking stability coefficient is decreased by 0.08. The results indicate the proposed strategy can better balance between braking energy recovery efficiency and braking stability than the conventional strategy.

Modeling and Simulation of Pure Electric Passenger Vehicle Based on MATLAB and AVL CRUISE

In this paper, the vehicle control strategy of pure electric passenger vehicle is designed in MATLAB/simulink, and the driving control strategy and the braking recovery mode control strategy modeling and Simulation are analyzed in detail. The model of the pure electric passenger car is built in AVL CRUISE software, and the parameters of the pure electric passenger car, driving motor, power battery, car tire and other modules are set, and then the established modules are connected. The results show that the drive control strategy of pure electric passenger vehicle does have its unique practicability and superiority.

Analysis of Regenerative Braking Strategy for Electric Vehicles Based on Braking Intention

Improved energy recovery during braking is the goal of the distributed drive electric car regenerative braking system. A regenerative braking control strategy for electric vehicles based on braking intention is suggested in order to address various drivers’ braking intents and road adhesion circumstances. An electric vehicle regenerative braking model for distributed drives is created using the MATLAB/Simulink tools. On the basis of FTP-75 operating conditions and open road operating conditions, the efficacy and economy of the control strategy in this study are verified. According to the various road adhesion coefficients, the simulation results demonstrate that the control method in this work can appropriately divide the braking torque of the wheels on both sides of the coaxial wheel. The technique can successfully enhance the regenerative braking recovery of distributed drive electric vehicles as compared to the often employed regenerative braking control method.

AUTOMATIC TEMPO CONTROL OF VEHICLE USING MULTI SENSORS

We have lost many precious lives daily due to road accidents. The main reasons are driver error, road situation, and vehicle condition. The system works to help drivers during emergencies and risks. The normal braking system is fully dependent on the driver will never prevent a collision in a sudden critical situation braking and the vehicle tends to crash. The autonomous braking system plays today a big role in accident prevention and the system is unfortunately only used in high cargo vehicles. The system also has speed limiter functions. It will decrease or increase vehicle speed depending on the obstacle distance from the moving vehicle to minimize damage or collision in an accident. The proposed algorithm is recovery braking and release braking based on the time to crash. The suggested design and system can be used in lower-class vehicles to reduce fatality using hybrid data and hybrid sensors. The goal of the research is to perceive the subject and stop the vehicle in an emergency.

Electrothermal Multicriteria Comparative Analysis of Two Competitive Powertrains Applied to a Two Front Wheel Driven Electric Vehicle during Extreme Regenerative Braking Operations

The powertrain performance in an electric vehicle is fully dependent on the electrical and thermal constraints of the static converters ensuring the power transfer taking place between the energy storage systems and the electromechanical machines. These constraints depend on the architectures of the power converters, and their control strategies. Particularly, the maximal limits are reached in maneuvers such as hard regenerative braking circumstances. Indeed, braking recovery is a critical phase in the vehicle’s operation, and its duration and intensity may strongly impact the vehicle’s battery behavior or integrated hybrid storage system. The innovative objective of the paper is to propose an electrothermal multicriteria comparative study based on electrical and thermal criteria for two competitive powertrains. These semi-active power configurations (a 3-level DC/DC converter-based, and a Z-source converter-based) are implemented in a two-front wheel driven electric vehicle during extreme regenerative braking conditions. Open-loop and closed-loop controls were implemented in the Z-source using the maximal constant boost control with 3rd harmonic injection modulation technique. We considered two paralleled IGBT modules instead of the single shoot-through structure. Our approach is based on simulation during an extreme braking maneuver leading to heavy repercussions on the overall powertrain system. The aim is to investigate the challenging structure of the Z-source. Results showed that the proposed 3-level DC/DC-based topology has better performances in terms of power losses, efficiency, thermal behavior, and electromagnetic interference.

Integrated energy management of hybrid power supply based on short-term speed prediction

The energy management strategy and output limitation of energy storage system affect the actual regenerative braking recovery. In order to optimize the performance and energy efficiency of vehicle energy storage system in the process of braking energy recovery, an integrated energy management strategy based on short-term speed prediction is proposed in this paper. Firstly, support vector machine classification method is used for off-line training and on-line recognition of driving patterns, and then input-output hidden Markov model and Gaussian mixture model are fused to establish speed prediction models under urban, suburban, and high-speed conditions for real-time prediction of speed sequences. Then, the power is distributed by the dynamic programming algorithm according to the short-term speed prediction results, and the distribution coefficient is corrected through the integrated strategy of braking force distribution and power distribution. Finally, the simulation results under continuously changing driving conditions show that the pattern recognition with changeable span is conducive to improving its accuracy during the transition period, and the proposed integrated energy management strategy is helpful to optimizing the performance of the hybrid energy storage system. The renewable energy utilization efficiency index indicates the efficiency of the integrated energy management strategy.

A Platoon Control Method Based on DMPC for Connected Energy-Saving Electric Vehicles

This article presents a distributed model predictive control (DMPC) algorithm with energy management for the electric vehicle platoon. In addition, a braking force distribution strategy is proposed for the following vehicles (FVs) in the platoon, and the optimal energy recovery braking force distribution is adopted within the limits permitted by braking regulations. The cost function of DMPC includes the following aspects: drive/brake power deviation, vehicle distance deviation, trajectory deviation, and energy consumption. Through the simulation analysis, it is demonstrated that the proposed algorithm has satisfactory speed and trajectory tracking performance, platoon stability, and driving comfort. Two platoon control methods [DMPC without energy management, proportion integration differentiation (PID)] and two single vehicle control methods (single vehicle with or without recovery braking) are designed to verify the proposed method. A semiphysical experimental platform is established to verify the authenticity, accuracy, and effectiveness of the model and the proposed control methods.

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

Based on the theory of the traditional hydraulic braking system of mining trucks and under the condition of safety, in order to maximize the regenerative braking energy recovery of hybrid mining trucks, a regenerative braking force distribution and control strategy for rear wheel parallel hybrid mining truck is proposed in this paper. Influences of charging current, battery state of charge value and braking force distribution on regenerative braking energy recovery is studied. ADVISOR is used for truck modeling and simulation under typical mining braking conditions. The results show that the maximum regenerative braking energy recovery rate is 65.01% when the initial charging current is 10A, 30A, 50A and 70A, respectively. The results indicate that the regenerative braking control strategy can solve the problems of braking safety performance and maximize the regenerative braking recovery rate.

A novel state energy spatialization regenerative braking control strategy based on Q- learning algorithm for a super-mild hybrid electric vehicle

ABSTRACT Most of the existing regenerative braking control strategies maintain the battery balance by the state of charge (SOC) penalty function. However, the SOC penalty function only realizes the instantaneous balance and ignores the global balance. To solve this problem, this paper proposes a novel state energy spatialization regenerative braking control strategy. Firstly, the battery energy is converted from the time domain to the space domain at each state. Based on the principle of balance between driving energy consumption and braking recovery energy, the mathematical model of referenced recovery energy is established. Then, considering the maximum energy recovery and the global battery energy balance, the return function is formulated, which takes the referenced recovery energy as the constraint condition. Subsequently, the proposed strategy is optimized by Q-learning algorithm and the optimal motor torques of regenerative braking are obtained. Finally, the Kullback–Leibler (KL) divergence rate is adopted to recognize the type of actual driving cycle, and the online optimal motor torque is obtained by looking up the corresponding table. Using the MATLAB/Simulink software, the simulation model of real working condition in Yubei district of Chongqing is established. The simulation results show that the SOC variation of the proposed strategy is 33.5% and 20.1% lower than that of the maximum energy recovery and DP strategy, respectively. The results indicate the proposed strategy maintains the global balance of battery energy better than the conventional strategy.

The wet braking and recovery behaviors of the P/M pad mated with C/C–SiC disc for high-speed trains

C/C–SiC ceramic is a promising braking material in high-speed trains. The research on wet braking is necessary for its application. In this paper, braking tests of C/C–SiC disc mated with powder metallic (P/M) pads were conducted under dry, wet and recovery braking conditions at initial braking speed (IBS) of 14, 22, 33, 44, 55 m/s. Coefficient of friction (COF) and surface morphologies under different conditions were discussed: The instantaneous COF under wet condition was lower but the instantaneous COF curves became smoother than those under dry condition. The difference between two conditions went smaller as IBS increased. Under recovery condition, it cost 33 stops at 14 m/s to recover to 93.1% of the origin COF. Meanwhile, 8 stops were needed at 55 m/s, and the recovery rate was 98.9%. When the IBS increased, the number of the stop needed was fewer and the recovery rate was higher. The surface morphologies further showed the braking under wet condition resulted in a smoother surface with less ploughing grooves and the disappearance of the friction film. Under the recovery condition, the surface became rough again with grooves and the friction film formed again. The results indicate that the wear debris were washed away by the sprayed water and the formation of friction film was inhibited. In addition, water film subsequently lubricated the friction surface, which reduced COF at low IBS. As IBS increased, high temperature accelerated the dewatering and evaporation of water and thus lead to the decrement of the COF difference between wet and dry friction which, in turn accelerated the recovery process.

Determination of optimal characteristics of braking energy recovery system in vehicles operating in urban conditions

The results of the research presented in this article characterize the influence of various factors on the current processes of the kinetic energy recovery system (KERS) for recovering kinetic energy of vehicles with electromechanical or electric drive (hybrid and electric cars) under braking. The article presents the basic limits of variations in accelerations and initial speeds during braking in urban traffic using WLTC (Worldwide harmonized Light-duty vehicles Test Cycles) as an example. Relationships affecting braking recovery are identified, which makes it possible to determine the power of the braking forces acting on a vehicle. Relationships between the initial braking speed, acceleration of deceleration, and recovery power are determined based on the relationships between the propulsion power and energy analysis. The resulting field of values for changes in regenerative braking power allows us to get an idea of the characteristics of KERS elements. The presented diagram describing changes in the maximum braking force power depending on the initial speed and acceleration of deceleration of a vehicle provides an insight into the possible ranges of the effective operation of the energy recovery system. As a result of a theoretical experiment, it was established that the vehicle mass affects the maximum power of regenerative braking. Based on the results of theoretical research, it is possible to determine the maximum current and power absorbed by an electric energy storage unit. The obtained relationship between the speed and acceleration in the process of active deceleration allows us to get an idea of the possible modes of charging the electric energy storage unit. Tests in road conditions, conducted with the use of several types of vehicles and test models with a hybrid engine, confirm the results of the research. The approaches presented in this article and the obtained results are indicative of the regularities of regenerative braking in vehicles operated in the road network, which makes it possible to select the optimal characteristics of an electric propulsion drive and ensure high fuel energy and environmental efficiency of vehicles at a minimum cost.

Research on the influence of the proportional relay valve on the economy and safety of the electric bus through the braking energy recovery system

ABSTRACT To research the influence of the proportional relay valve on the economy and safety of the electric bus through the braking recovery system, a proportional relay valve model was proposed. Based on the analysis of the structure and working principle of the solenoid on/off valve, a dynamic model of “electro-magnetic-machine-air” coupling was simulated and analyzed. Then, based on the solenoid on/off valve and proportional relay valve, two pressure regulator modules were designed, the braking energy recovery system schemes were designed, respectively. Fuel economy tests were carried out under China city bus typical driving cycle based on two kinds of air pressure regulating module to research the influence of the proportional relay valve on the economy of the electric bus. An integrated control system of braking energy recovery and anti-lock braking system based on the proportional relay valve was proposed, hardware-in-the-loop braking energy recovery system contrast tests of the anti-lock braking system were also carried out based on two kinds of air pressure regulating module. The test results indicated that the proposed braking energy recovery system schemes were effective. The test results also demonstrated the economic contribution rate of the braking energy recovery of the proportional relay valve pneumatic control module was slightly higher than that of the proportional relay valve. Meanwhile, the proportion relay valve pressure regulating module achieved a good target speed follow and the accurate adjustment of air pressure in anti-lock braking system control.

Braking/steering coordination control for in-wheel motor drive electric vehicles based on nonlinear model predictive control

Braking and steering are common maneuvers performed by drivers during driving. This paper presents a hierarchy control strategy to coordinate the braking and steering performance for in-wheel motor drive electric vehicles (IWMD EVs). A particle swarm optimization-based nonlinear predictive control (PSO-NMPC) scheme is proposed to calculate the required longitudinal force, lateral force and yaw moment of the vehicle in the upper controller. In the lower controller, the PSO algorithm is again utilized to realize the required forces and yaw moment through optimal torque allocation and brake actuator regulation while maintaining vehicle stability and maximizing the regenerative braking recovery. A fault-tolerance mechanism is also incorporated to enhance the robustness of the proposed method. Finally, the effectiveness of the proposed scheme is examined under various braking execution scenarios through the Carmaker-Simulink co-simulation. The results show that the proposed scheme outperforms other state-of-the-art methods in all-round aspects.

Design of Parallel Braking Control System for Port Hybrid Electric Vehicle

ABSTRACT Zhang, Z., 2018. Design of parallel braking control system for port hybrid electric vehicle. In: Liu, Z.L. and Mi, C. (eds.), Advances In Sustainable Port And Ocean Engineering. Journal of Coastal Research, Special Issue No. 83, pp. 513–519. Coconut Creek (Florida), ISS N 0749-0208. Conventional port hybrid vehicles can't effectively recycle tremendous kinetic energy brought by car brake due to the limitation of energy storage element and energy conversion form in energy recovery braking system. A parallel hydraulic hybrid power control system is designed to solve the contradiction between braking safety stability and realizing the maximum energy recovery. The linear proportional electromagnetic valve is adopted to control the hydraulic pressure of the hydraulic cylinder of the brake. The numerical control of the frictional braking force is realized, and the braking force control strategy can be realized with the braking control system. The experimental results show that the system improves the s...

Electric Vehicle Energy Flow Analysis and Energy Saving Technology Research

Energy saving research is the development trend of electric vehicles, which is the key technology for the large-scale industrialization of electric vehicles. Based on the vehicle dynamic simulation models, energy flow and dissipation mechanism was analyzed. The proportions of main components to energy consumption were analyzed with experimental verification. Through the vehicle matching optimization and the low rolling resistance coefficient tires selecting, also to reduce the weight of vehicle, improve the body design to effectively reduce the air resistance coefficient, and select the appropriate braking recovery strategy to optimize the energy consumption. Finally, through comprehensively optimization simulation, the vehicle energy consumption was improved significantly.

Energy recovery based on pedal situation for regenerative braking system of electric vehicle

ABSTRACTEnergy recovery is a key technology to improve energy efficiency and extend driving range of electric vehicle. It is still a challenging issue to maximise energy recovery. We present an energy recovery mode (mode A) which recovers braking energy under all situations that accelerator pedal (AP) is lifted, brake pedal (BP) is depressed, as well as AP and BP are released completely; and propose a control strategy of regenerative braking based on driver's intention identified by a fuzzy recognition method. Other two modes: (1) recovery braking energy only the BP is depressed (mode B), (2) no energy recovery, have been studied to compare with mode A. Simulations are carried out on different adhesion conditions. Recovered energy and driving range are also obtained under FTP75 driving cycle. Road test is implemented to validate simulation results. Results show that mode A can improve energy recovery by almost 15.8% compared with mode B, and extend driving range by almost 8.81% compared with mode B and 20.39% with the mode of no energy recovery; the control strategy of regenerative braking can balance energy recovery and braking stability. The proposed energy recovery mode provides a possibility to achieve a single-pedal design of the electric vehicle.

Downshift decision and process optimal control of dual clutch transmission for hybrid electric vehicles under rapid braking condition

Abstract Hybrid electric vehicles (HEVs) equipped with dual clutch transmission (DCT) can benefit from engine auxiliary braking force and driving motor regenerative braking force in braking conditions. This can effectively reduce the workload of hydraulic mechanical braking systems and recovery braking energy, which will improve the fuel economy. In the downshift process, the driving motor is involved to response the change of torque/speed demand, which can further improve the shift quality of DCT without affecting the engine emissions and fuel economy. The combined braking condition of HEVs with DCT allows for the variation of power distribution between the front and rear axle, as well as the electric and hydraulic braking force. In this study, the downshift decision strategy is designed based on the two-parameter shift schedule, while considering the driver’s subjective driving intention. Subsequently, the mathematical model developed to investigate the downshift process of HEVs with dual clutch transmission has been applied to skip downshift process, to analyze the control sequence and implement different control algorithms according to respective control objects. Specifically, the sliding mode variable structure optimization control algorithm is used to allow the engine speed to track the target value in the torque phase. In addition, the linear quadratic tracking controller and the model reference adaptive system are used, based on adjustable parameters, to realize the speed synchronization of the clutch driving and driven plate in the inertial phase. According to the results of electro-hydraulic braking force distribution, the braking forces of an integrated starter generator (ISG) motor and hydraulic brake system are controlled to switch to the demand level. Then, the simulation model established on a Matlab/Simulink platform is used to validate the skip downshift control strategy. Finally, the designed control strategies are verified on the test bench. The test results demonstrate that the established shift control strategy can achieve the target power downshift under braking conditions, and have a good downshift quality, which lays a foundation for subsequent development and real vehicle tests.