Braking Energy Recovery Efficiency Research Articles

Control strategy and parameter optimization of compound energy storage device for pure electric vehicle

In order to solve the problem of insufficient power of battery of pure electric vehicle, we study the energy storage system of electric vehicle. According to the characteristics and objectives of the complex energy storage device, we design its working mode, and propose a fuzzy control strategy based on speed and current limitation. In order to further improve the vehicle performance and reduce the output current of the battery, the key parameters of the composite energy storage device are linearly optimized. The simulation results show that: The acceleration time of pure electric vehicles equipped with composite energy storage devices is shortened by 12%, the braking energy recovery efficiency is increased by 39%, the power consumption of 100 kilometers is reduced by 8.55%, and the output current of the battery is significantly reduced, effectively extending the service life of the battery and the driving range of the vehicle.

A Logic Threshold Control Strategy to Improve the Regenerative Braking Energy Recovery of Electric Vehicles

With increasing global attention to climate change and environmental sustainability, the sustainable development of the automotive industry has become an important issue. This study focuses on the regenerative braking issues in pure electric vehicles. Specifically, it intends to elucidate the influence of the braking force distribution of the front and rear axles on access to energy recovery efficiency. Combining the I curve of a pure electric vehicle and the boundary line of the Economic Commission of Europe (ECE) regulations, the braking force distribution relationship between the front and rear axles is formulated to satisfy braking stability. The maximum regenerative braking force of the motor is determined based on the motor torque characteristics and battery charging power, and the regenerative braking torque is optimized by combining the constraints of the braking strength, battery state of charge (SOC), and vehicle speed. Six road working conditions are built, including the New European Driving Cycle (NEDC), the World Light-Duty Vehicle Test Cycle (WLTC), Federal Test Procedure 72 (FTP-72), Federal Test Procedure 75 (FTP-75), the China Light-Duty Vehicle Test Cycle—Passenger (CLTC-P), and the New York City Cycle (NYCC). The efficiency of the regenerative braking strategy is validated by using the Simulink/MATLAB simulation. The simulation results show that the proposed dynamic logic threshold control strategy can significantly improve the energy recovery effect of electric vehicles, and the energy recovery efficiency can be improved by at least 25% compared to the situation without regenerative braking. Specifically, under the aforementioned road working conditions, the braking energy recovery efficiency levels are 27.69%, 42.18%, 49.54%, 47.60%, 49.28%, and 51.06%, respectively. Moreover, the energy recovery efficiency obtained by the current dynamic logic threshold is also compared with other published results. The regenerative braking control method proposed in this article makes the braking control of electric vehicles more precise, effectively reducing energy consumption and improving the driving range of electric vehicles.

Anti-lock braking control using an interval type-2 fuzzy neural network scheme for electric vehicles

Control precision and robustness can be regarded as essential challenges of slip ratio control because of the external uncertainties of road conditions and the internal delay response of braking actuators. In addition, it is difficult to obtain a trade-off between braking energy recovery efficiency and braking safety under some extreme braking conditions. To synchronously improve both slip ratio control and braking energy recovery efficiency for different road conditions, an anti-lock braking system (ABS) using a novel interval type-2 fuzzy neural network (IT2FNN) control scheme is proposed for electrohydraulic braking systems. The novel IT2FNN control scheme with five layers is designed to calculate the commanded braking torque. The membership function layer utilizes type-2 fuzzy sets to describe the slip ratio error degree, which enhances the scheme’s anti-interference ability, and the enhanced Karnik-Mendel (EKM) algorithm is used in the type-reduction layer to accelerate computation. Additionally, the network adjusts the parameters of the membership function and rules by decreasing the performance function value corresponding to the braking torque error to improve slip ratio control and enhance the self-adaptation capacity. Simulations showed that IT2FNN control can not only improve slip ratio control performance and decrease the braking torque error but also enhance the energy recovery efficiency of regenerative braking on different road surfaces.

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.

Research on Composite Braking Mode Switching Strategy Based on Fuzzy Algorithm

AbstractAiming at the cruising range of electric vehicles, this paper proposes a control strategy for electric vehicle electromechanical composite braking mode switching based on motor braking force correction. The braking force of the motor is adjusted by factors such as braking intensity to improve the braking energy recovery, and the braking force distribution curve is designed considering the braking energy and braking safety and stability. The research results show the braking time, braking torque, and battery charge. The peak value of discharge current has been improved, and the braking energy recovery efficiency has increased by 9.17% and 3.32% respectively under different working conditions. Under different braking modes with an initial speed of 30 km h−1, the braking energy recovered by the battery has increased by 16.04 , 3.89, 9.63 kJ, the braking time and braking distance are also shorter, which highlights the superiority of this control strategy.

Research on Compound Braking Control Strategy of Extended-Range Electric Vehicle Based on Driving Intention Recognition.

To improve the braking performance and braking energy feedback rate of extended-range electric vehicles, a driving intention recognition model is established based on Markov theory with brake pedal displacement, pedal displacement change rate, and pedal force as parameters, and the validity of the model is verified by actual vehicle test data. Based on the driving intention recognition model, a compound braking control strategy for extended-range electric vehicles is established with the constraints of braking force distribution and motor and battery characteristics. Cruise and MATLAB are used for joint simulation. The simulation results show that the compound braking system of extended-range electric vehicles with the compound braking control strategy based on brake intention recognition can work stably and effectively. On the premise of ensuring braking stability and safety, the braking energy recovery efficiency can be increased by 0.36% and the recovery rate can reach 12.88%. The compound braking system can effectively recover braking energy, improve the energy utilization rate of extended-range electric vehicles, and increase driving range.

Strategy Design and Performance Analysis of an Electromechanical Flywheel Hybrid Scheme for Electric Vehicles

Energy management strategies are one of the key factors affecting the working efficiency of electric vehicle energy power systems. At present, electric vehicles will develop real-time and efficient energy management strategies according to the topology of on-board energy power system to improve the driving performance of vehicles. In this paper, a new electromechanical flywheel hybrid system is studied. Firstly, the characteristics of the topological scheme of the electromechanical flywheel hybrid system are analyzed, and the working modes are designed. Secondly, in order to improve the efficiency of vehicles’ energy utilization and ensure the real-time performance of the management strategy, an energy management strategy based on fuzzy rules is designed with the flywheel’s state of energy (SOE) as the key reference parameter. Then, considering the directional stability in the braking process, the braking force distribution strategy between the front axle and the rear axle is designed. In order to improve the braking energy recovery efficiency, the secondary distribution strategy consisting of a mechanical braking force and regenerative braking force on the front and rear axles is designed. Finally, the bench test of a electromechanical flywheel hybrid system is carried out. Experiments show that compared with the original dual-motor four-wheel drive scheme, the electromechanical flywheel hybrid four-wheel drive system scheme developed in this paper can reduce the current variation range of lithium batteries by 43.16%, increase the average efficiency by 1.04%, and increase the braking energy recovery rate by 40.61% under the Japan urban cycle conditions. In addition, taking advantage of the energy and power regulation advantages of the electromechanical flywheel device, the power consumption of the lithium battery is reduced by 1.82% under cycling conditions.

Study on Speed Planning of Signalized Intersections with Autonomous Vehicles Considering Regenerative Braking

In order to reduce the energy consumption caused by the frequent braking of vehicles at signalized intersections, an optimized speed trajectory control method is proposed, based on braking energy recovery efficiency (BERE) in connection with an automated system for vehicle real-time interaction with roadside facilities and regional central control. Our objectives were as follows; firstly, to establish the simulation model of the hybrid energy regenerative braking system (HERBS) and to verify it by bench test. Secondly, to build up the genetic algorithm (GA) optimization model for the deceleration stopping of the HERBS. Then, to obtain signal light status and timing information to be the constraints; the BERE is to be the optimized objective, resulting in optimization for the speed trajectory under the deceleration stopping condition of a single signalized intersection. Finally, vehicle simulations in ADVISOR software are utilized to validate the optimization results. The results show that the BERE during deceleration stopping at a single signalized intersection after the speed trajectory optimization is 36.21% higher than that of inexperienced drivers, and 7.82% higher than that of experienced drivers.

Research on Braking Efficiency of Master-Slave Electro-Hydraulic Hybrid Electric Vehicle

To address the problems of short-rangee and poor braking safety of electric vehicles, this paper proposes a master-slave electro-hydraulic hybrid passenger car drive system based on planetary gear. The system couples the electrical energy output from the electric motor with the hydraulic energy output from the electro-hydraulic pump/motor through the planetary gear. The hydraulic system is used as the auxiliary power source of the power system giving full play to the advantages of the hydraulic system and the electric system. After theoretical analysis, this paper establishes a master-slave electro-hydraulic hybrid electric vehicle (MSEHH-EV) model based on planetary gear in AMESim software. A braking energy recovery control strategy is designed with the maximum braking energy recovery efficiency as the target. Braking strength determines the switching of braking modes. Finally, comparing the certified pure electric vehicle (EV) model in AMESim, we are able to substantiate the superiority of the strategy proposed in this paper. The simulation results revealed that the battery consumption rate of the new power vehicle is reduced by 17.766%, 11.358%, and 9.427% under UDDS, NEDC, and WLTC conditions, respectively, which supports the range. At the same time, the braking distance is significantly shortened, and the maximum braking distance is shortened by 15.65 m, 21.97 m, and 21.45 m, respectively, under the three operating conditions, which improves the braking safety.

Interval Type-2 Fuzzy Logic Anti-Lock Braking Control for Electric Vehicles under Complex Road Conditions

To simultaneously track the ideal slip rate and realize ideal energy recovery efficiency under different complex road conditions, an electro-hydraulic compound anti-lock braking system based on interval type-2 fuzzy logic control strategy and its corresponding braking torque allocation strategy have been developed for electric vehicles. The proposed interval type-2 fuzzy logic controller aims to calculate the ideal total braking torque by four steps, namely, fuzzification, fuzzy inference, type reduction, and defuzzification. The slip rate error and the change rate of slip rate error are utilized as inputs in the fuzzification, and then, the membership degree interval of fuzzy variables determined by the upper and lower membership functions is used to calculate the activation degree interval of different fuzzy rules in the fuzzy inference process, which enhances the anti-interference ability to external uncertainties and internal uncertainties. The braking torque allocation strategy is proposed to maintain the maximum energy recovery efficiency on the premise of safe braking. The software of MATLAB/Simulink is applied to simulate the process of anti-lock braking control under two complex road conditions. Simulation results corroborate the proposed interval type-2 fuzzy logic anti-lock braking control system can not only obtain better slip rate control effect and outstanding robustness but also achieve ideal regenerative braking energy recovery efficiency under both joint-μ and split-μ road surfaces.

Energy Management Strategy for an Electromechanical-Hydraulic Coupled Power Electric Vehicle Considering the Optimal Speed Threshold

Considering the problems of the low energy recovery efficiency and the short driving range of pure electric vehicles, a new electromechanical–hydraulic coupled power electric vehicle is proposed. First, we develop an electromechanical–hydraulic coupled power electric vehicle model and design an energy management strategy to match it. On this basis, an optimization strategy is proposed with the goal of improving the braking energy recovery efficiency and avoiding the impact of high-speed braking energy recovery on the hydraulic system. The energy recovery mode conversion is optimized for different vehicle speeds when braking. Finally, the proposed optimization strategy is verified by joint simulation. The results show that when the vehicle speed is higher than 10 m/s for energy recovery mode switching, the total recovery efficiency of the whole vehicle increases to 97.273% and the SOC of the power battery increases by 0.14%. This provides strong support for improving the driving range of electromechanical–hydraulic coupled power electric vehicles.

Regenerative braking control under sliding braking condition of electric vehicles with switched reluctance motor drive system

To enhance braking energy recovery and improve braking comfort under sliding braking condition for electric vehicles (EVs) with switched reluctance motor (SRM), a novel regenerative braking control scheme based on braking force optimization controller and angle optimization controller is presented in this paper. Firstly, the current regulation method is developed, and the braking torque control strategy with four-phase currents and voltages of SRM drive system is proposed. Braking system (BS) of EVs including mechanical braking system and regenerative braking system is established. Then, the multi-objective optimization strategy (MOOS) for vital control parameters of regenerative braking system is proposed to improve regeneration braking comprehensive performance under sliding braking condition of EVs, where braking energy recovery efficiency, braking impact, and current fluctuation are considered as indexes to reflect working distance, braking smoothness, and battery lifetime of EVs, respectively. Furthermore, braking force optimization controller and angle optimization controller are developed by means of the multi-objective optimization results. Finally, compared to the efficiency optimization, the braking comfort optimization, and the current smoothness optimization strategy, the regenerative braking control scheme with MOOS can effectively increase working distance, improve braking smoothness, and extend battery lifetime of EVs under sliding braking condition. Furthermore, the real-time performance and effectiveness of the braking torque control strategy proposed are verified by simulation and PIL test.

Regenerative Braking Control Strategy of Electric Vehicles Based on Braking Stability Requirements

Electric vehicles are effective way to solve energy and environmental problems, but the promotion and application of electric vehicles are suppressed by their limited endurance range seriously. The regenerative braking technology is an important method to increase the endurance range of the electric vehicle. During the braking process, the kinetic energy of the electric vehicle can be converted into electric energy and stored in the energy source device with the regenerative braking system, so the endurance range of the electric vehicle can be increased accordingly. In order to increase the efficiency of energy recovery, a regenerative braking strategy with the optimization distribution algorithm is proposed in this paper, and the braking forces of the front and rear axles are distributed optimally with variable ratios based on the braking strength. With the optimal braking force distribution ratio and related constraint conditions, the regenerative braking control strategy was designed to meet the braking stability and the maximum braking energy recovery. And then a simulation model of the braking control strategy was built with MATLAB/Simulink software, and the simulation tests on UDDS and NEDC cycle conditions were done to verify the effectiveness of the designed regenerative braking control strategy. Compared with the control strategy of ADVISOR software, the braking energy recovery efficiency was improved more than 51.9 % while maintaining the braking stability.

Research on the Coordinated Control of Regenerative Braking System and ABS in Hybrid Electric Vehicle Based on Composite Structure Motor

An antilock braking system (ABS) can ensure that the wheels are not locked during the braking process which is an important system to ensure the safety of braking. Regenerative braking is also a crucial system for hybrid vehicles and helps to improve the cruising range of the car. As such, the coordinated control of a braking system and an ABS is an important research direction. This paper researches the coordinated control of the regenerative braking system and the ABS in the hybrid vehicle based on the composite structure motor (CSM-HEV). Firstly, two new braking modes which are engine-motor coordinated braking (EMCB) and dual-motor braking (DMB) are proposed and the coordinated control model of regenerative braking and ABS is established. Then, for the purpose of optimal operating efficiency and guaranteeing the vehicle brake slip rate, a braking force distribution strategy based on predictive control algorithm is proposed. Finally, the Simulink model is established to simulate the control strategy. Results show that the slip rate can well track the target and ensure the efficient operation of the system. Compared with the normal braking mode, the braking energy recovery rate of EMCB is similar, but it can reduce the fuel loss of the engine during the braking process by 30.1%, DMB can improve the braking energy recovery efficiency by 16.78%, and the response time to track target slip is increased by 12 ms.

Dynamic Coordinated Control for Regenerative Braking System and Anti-Lock Braking System for Electrified Vehicles Under Emergency Braking Conditions

The economy of electrified vehicles can be improved by using the motor to recover the energy released during braking. However, the vehicle’s regenerative braking system (RBS) and anti-lock braking system (ABS) are not compatible, so the energy dissipated during braking cannot be recovered under emergency braking conditions. This paper employs the method of logic threshold control combined with phase plane theory to analyze the relationship between the slip rate and the braking torque during the ABS braking process and to obtain the composition rule of the braking torque required for ABS braking. Based on this rule, a control strategy to coordinate RBS and ABS when triggering ABS is proposed to improve the efficiency of braking energy recovery. Furthermore, a comparative simulation is conducted to analyze the braking performance of electrified vehicle on roads with different adhesion coefficients by adopting the proposed control strategy and the traditional control strategy. The results show that, compared with the traditional coordinated control strategy, the braking energy recovery efficiency of the proposed coordinated control strategy is improved by 23.08%-38.54%, and can effectively shorten the braking distance and braking time, with better braking performance. Therefore, this paper offers a useful theoretical reference to the design of RBS and ABS coordinated control strategies for electrified vehicles.

A Survey of Brake-by-Wire System for Intelligent Connected Electric Vehicles

Intelligent connected electric vehicles (EVs) are widely considered as a trend in the global automotive industry to make transportation safer, cleaner and more comfortable. As an important component of intelligent connected EVs, the brake-by-wire (BBW) system is the key to determining the performance of the vehicle and the efficiency of braking energy recovery. BBW systems are showing great promise in the area of vehicle braking due to the increasing requirements on safety and energy efficiency of vehicles. In recent years, BBW systems have undergone great changes in terms of structure and control methods, not only increasing safety and energy recovery efficiency, but also integrating more functions. Although important advancements have been achieved in this field, these works have not been fully summarised. This paper surveys and summarizes the research in literature to bring topical information to the field of intelligent transportation systems. The objective of this study is to present an overview of both the development trend and key technologies of the BBW system for intelligent connected EVs. Firstly, the development, structure and core components of BBW system are described. Secondly, the control method and control strategy of BBW system are analyzed. As much as the system shows great promise, the problems existing on its current technology should be addressed as well. Finally, some important countermeasures are proposed to solve the existing technical problems of the BBW system.

Regenerative Braking Control Strategy for Electric Vehicles Based on Optimization of Switched Reluctance Generator Drive System

To improve braking performance and regenerative energy of front drive electric vehicles (EVs) driven by switched reluctance motor (SRM), a regenerative braking control strategy based on multi-objective optimization of switched reluctance generator (SRG) drive system is proposed in this paper. Firstly, a partition braking force distribution strategy is developed by jointly considering braking energy and safety, and SRG drive system model is established based on low and high-speed condition. The vehicle braking system model including mechanic and regenerative braking system is built. Then, a multi-objective optimization function with three weight factors is defined, where output generated power, torque smoothness, and current smoothness are selected as optimization objectives to improve the driving range, braking comfort, and battery lifetime, respectively. Furthermore, a multi-objective optimization controller with variable switch angles is designed and combined with vehicle braking system. Finally, braking energy recovery efficiency, braking smoothness, and charging current smoothness under the multi-objective optimization controller for SRG are analyzed and compared with those under output power optimization controller. The comparison results show that the regenerative braking control strategy based on multi-objective optimization of SRG can effectively increase the vehicle braking comfort and improve battery lifetime without decreasing recovery energy.

Research and simulation of energy control strategy for pure electric vehicle based on advisor

This paper is based on the simulink and advisor2002 simulation software, aiming at the energy control strategy of pure electric vehicle whose energy storage system is composed of batteries and ultracapacitors in parallel. In order to improve the efficiency of braking energy recovery, a hybrid energy system model was built and a fuzzy control based energy allocation strategy was established. The hybrid energy system can reasonably distribute the energy output ratio of batteries and ultracapacitors, and improve the system performance.

Hybrid energy storage system and energy distribution strategy for four-wheel independent-drive electric vehicles

This paper presents a novel topology of a hybrid energy storage system (HESS) and an improved energy distribution control strategy for four-wheel independent-drive electric vehicles (4WIDEVs) to improve their energy efficiency and dynamic performance under urban driving conditions. The small 4WIDEV was developed for only urban driving conditions and was limited to a maximum speed of 60 km/h. The HESS consists of a battery, four ultracapacitor (UC) groups and five direct current/direct current (DC/DC) converters. The 4 UC groups of the proposed HESS have two connection modes under braking conditions, namely a series-connected recovery structure (SCRS) and a parallel-connected recovery structure (PCRS). By changing the voltage ratio between the low-voltage and high-voltage sides of the DC/DC converters, the conversion efficiency can be improved, and thus, the braking energy can be effectively recovered. The upper and lower limits of the state of charge (SOC) of the UC are estimated according to the vehicle speed, and associated energy distribution rules are established to achieve a reasonable energy distribution between the battery and the UC. The proposed composite power system and energy distribution strategy were simulated, and a hardware-in-the-loop experiment was carried out on the experimental vehicle. The simulation and experimental results show that under urban driving conditions, the HESS can fully utilize the characteristics of UC, charging and discharging quickly with large current; to meet the instantaneous high power demand of electric vehicles, improve the power performance of electric vehicles, and protect the battery from the impact of large currents. The braking energy recovery efficiency of the vehicle increased by 13.53% in the simulation and by 10.26% in the experimental vehicle test.

Optimization of the Efficiency of Braking Energy Recovery in Rail Transport by Changing Arrival Time

Optimization of the Efficiency of Braking Energy Recovery in Rail Transport by Changing Arrival Time