Regenerative Braking System Research Articles

ELECTRIC VEHICLE INTEGRATED WITH PMSM AND REGENERATIVE BRAKING SYSTEM SPEED EVALUATION BASED ON DIVERSE CONTROL STRATEGIES

The choice of a vehicle speed controller for a permanent magnet synchronous driven battery electric vehicle (BEV), integrated with a regenerative braking system (RBS), plays a pertinent role in how far a vehicle can travel. While many studies have implemented varied control strategies, the proportional-integral (PI) based controller is predominately studied and practically used. Generally, the performance of PI controller compared to Modeled Predictive Controller; Reference Tracking Signal Controller Based on Generated Polynomial and Reference Tracking Signal Controller Based on Controlled Polynomial in a permanent magnet synchronous motor (PMSM) driven battery electric vehicle integrated with RBS speed control based on field-oriented control mechanism is lacking. In order to address that shortcoming, this paper aims to investigate the performance of a PI controller compared to generalized predictive controllers based on the difference between a reference speed and a controlled speed of the battery electric vehicle. The performance for each controller considered was evaluated in terms of the state of charge (SOC), R^2, slip ratio, minimum error metrics, and peak speed using real-time driving scenario factoring braking, throttling, wind speed, and cruise effects for 15 s. The results show that the PI controller outperforms the other controllers on most metrics. Except for the peak SOC, slip ratio, and peak speed, the Reference Tracking Signal Controller Based on Generated Polynomial seems to be better, although with a drawback of the highest error metrics. Generally, all the controllers yielded excellent regenerative braking effects in SOC and effective control of the speed trajectory.

A novel electro-hydraulic compound braking system coordinated control strategy for a four-wheel-drive pure electric vehicle driven by dual motors

The electro-hydraulic compound braking system of a pure electric vehicle can recover the energy released during braking and store it in the battery through the motor, thereby improving the vehicle's energy utilization efficiency. However, how to coordinate the control of motor braking and hydraulic braking during vehicle braking to ensure the optimal balance of vehicle braking safety and energy recovery efficiency is still an urgent problem to be solved in the field of new energy vehicles. This paper takes the four-wheel-drive pure electric vehicle driven by dual motors as the research object and proposes a coordinated control strategy for an electro-hydraulic hybrid brake system with efficient energy recovery. The proposed coordinated control strategy is composed of two parts: the braking force distribution control strategy that comprehensively considers braking safety and charging efficiency optimization and the coordinated control strategy of regenerative braking system (RBS) and anti-lock braking system (ABS) based on model predictive control. The results show that the proposed coordinated control strategy has superior braking performance, and improves the energy recovery efficiency by more than 22.76% compared with the conventional coordinated control strategy, proving the effectiveness of efficient energy recovery under the premise of ensuring stability and safety.

An adaptive fuzzy sliding‐mode control for regenerative braking system of electric vehicles

SummaryThis article proposes a novel fuzzy sliding‐mode control scheme under an adaptive control strategy for energy management mechanism in electric vehicles that are subject to a regenerative braking system. The effectiveness of the fuzzy logic controller is to adjust the sliding mode parameters according to the slip ratio tracking error between the optimal slip ratio and the actual slip ratio. Specifically, the proposed torque distribution strategy can integrate the best battery condition and energy recovery efficiency under the practical constraints through this control method by fixing the pneumatic braking torque and motor torque. Finally, an electric vehicle model is established in the Simulink environment to verify the applicability of the proposed control algorithm.

A Peer Review of Hybrid Electric Vehicle Based on Step-Up Multi-input Dc-Dc Converter and renewable energy source

Due to the rapid increase of environmental pollution caused by automobiles. To decrease pollution and to save our resources, there is an alternator to use an electric vehicle instead of a gasoline engine. The main drawback of a gasoline engine of compared to the electric vehicle can polluter noise efficiency durability. When it comes to durability, efficiency, and acceleration capabilities of electric vehicles, they are more impressive. The electric vehicles involve HEVs and BEVs. Generally, ultra-capacitor, solar Photovoltaic (PV) system, batters, regenerative braking systems and flywheel are utilized in HEVs as energy storage devices. All energy storage devices are linked to this distinct dc-dc converter scheme for raising input sources’ voltage. In past few decades, most HEVs have incorporated multi-input converters in order to enhance their reliability and efficiency. There are several distinct multi-input dc-dc converter schemas utilized in HEVs. This research discusses their current and future trends as well as energy storage devices.

Performance Analysis of PI and DMRAC Algorithm in Buck–Boost Converter for Voltage Tracking in Electric Vehicle Using Simulation

This study introduces a Direct Model Reference Adaptive Control (DMRAC) algorithm in a buck–boost converter in the power distribution of an electric vehicle. In this study, DMRAC was used in order to overcome the system nonlinearity due to load demand variation, in case of different driving modes (such as acceleration, stable and regenerative braking system mode), and the presence of disturbances in the system. DMRAC receives popularity because of its robustness in the presence of nonlinearity and ensuring system stability. To evaluate the efficacy of DMRAC in the current system, its performance was compared with a PI controller in the MATLAB/Simulink environment. The simulation results show the superiority of DMRAC over a conventional PI control approach, in both variable load demand and disturbed system cases that were measured by tracking error. The improvement was seen in the DMRAC response, with smaller tracking error and faster transient and disturbance rejection. The main contribution of this work is in introducing DMRAC, particularly in a buck–boost converter, and its efficacy with a DC–DC converter for an electric vehicle, which has not been studied before.

Adaptive distributed finite‐time fault‐tolerant controller for cooperative braking of the vehicle platoon

Vehicle platooning can significantly reduce traffic accidents and enhance transportation safety. Among many subsystems and functionalities equipped in a vehicle platoon, cooperative braking is a safety-critical one. Besides, as actuator faults would deteriorate vehicle safety and stability, they pose a great challenge to the platoon, particularly during cooperative braking. To address the aforementioned problems, this study designed an adaptive distributed finite-time fault-tolerant controller for vehicle platoons under cooperative braking condition. First, based on the graph theory and vehicle longitudinal dynamics, the cooperative braking model of a platoon is constructed. Then, the models of hydraulic braking system and regenerative braking system are developed with malfunction analysis. Based on the vehicle's fault model and the representation of the platoon consensus errors, an adaptive finite-time sliding-mode fault tolerant controller is proposed to maintain consensus between vehicle's states during fault occurring. Further, a distributed adaptive law is presented considering the parameter estimation error and sliding-mode surface. The finite-time convergence property and the stability of the proposed controller are demonstrated. Numerical simulations are conducted under different conditions. The simulation results reflected by the control performance and actuators' responses validate the feasibility and effectiveness of the designed control method.

A comprehensive review on energy storage in hybrid electric vehicle

The sharp inclination in the emissions from conventional vehicles contribute to a significant increase in environmental issues, besides the energy crises and low conversion efficiency leads to the evolution of electric vehicles (EV). Hybrid electric vehicles (HEV) have efficient fuel economy and reduce the overall running cost, but the ultimate goal is to shift completely to the pure electric vehicle. Despite this, the main obstruction of HEV is energy storage capability. An EV requires high specific power (W/kg) and high specific energy (W·h/kg) to increase the distance travelled and reduce the time required for charging. The main focus of this paper is on the energy sources as these are the main components in EVs towards making them eco-friendly and cost-effective. Various topologies of EV technology such as HEVs, plug-in HEVs, and many more have been discussed. These topologies of EVs are based on the diverse combination of batteries, fuel cells, super-capacitor, flywheels, regenerative braking systems, which are used as energy sources and energy storage devices. • A review on various topologies of electric vehicle based on energy sources. • An overview on operating principles of energy storage system with its management. • An overview on challenges involved in adaptation of energy storage system.

Research on Cooperative Braking Control Algorithm Based on Nonlinear Model Prediction

To address the coordinated distribution of motor braking and friction braking for the regenerative braking system, a cooperative braking algorithm based on nonlinear model predictive control (NMPC) is proposed, with braking energy recovery power, tire slip rate, and motor torque variation as the optimization objectives, and online optimization of the coordinated distribution of motor braking and friction braking. Using the offline model built in Matlab/Simulink, the cooperative braking algorithm is tested for energy efficiency and braking safety. The results show that when based on World Light Vehicle Test Cycle (WLTC), the energy recovery rate can reach 30.4%, and with a single high braking intensity, the braking safety can still be ensured.

Design of HMI Based Digital Electric Bike Using DC/AC Power Converter with Regenerative Feature

The research project introduces an efficient HMI-based digitally controlled electric bike hardware model. Thesystem is designed using power electronics and LCD touch control. A low-cost model with regenerative features increases the acceptance of electric vehicles in Pakistan. The country is facing grave environmental issues and the transport sector has a major role in polluting the environment. Technology also promotes the environment-friendly electric vehicles Industry and reduces the growing pollution problem of the country. Economical transport with feasible milage is an essential need of the current time. Research provides the effective Electric-bike with digital security and improved mileage. A Six-Step DC/AC power converter drives the low consumption BLDC motor. The project analyzed the real-time performance of the electric vehicle on HMI. A regenerative braking system generates power while reducing the speed of a moving electric bike. The modeling andsimulation are performed using Proteus/Multisim simulating software. Results are verified using a hardware test model. The results will be helpful for design commercial advance HMI-based electric bikes in terms of motor requirement, machine behaviour, charging/discharging analysis at a different speed and torque, charging the battery while driving, and their limitations.

Research on regenerative braking system for linear control chassis platform

The regenerative braking system of the electric vehicle with the linear control chassis plays an important role in improving the mileage of the vehicle, which mainly solves the problem of large electricity demand for the linear control chassis. After analyzing the structural characteristics of the linear control chassis, the constraints of regenerative braking and the existing regenerative braking control strategies, a new regenerative braking control strategy is proposed, and the control strategy is modified. The regenerative braking control strategy model is established by Simulink / Stateflow, and the braking effect and energy recovery efficiency are verified by changing the initial braking speed. The simulation results show that the strategy can well complete the braking task of the vehicle, and the braking energy recovery rate increases with the increase of the initial braking speed. Reasonable control strategy can effectively improve vehicle energy recovery efficiency.

Survey on Regenerative Braking in Electrical and Hybrid Vehicles

Abstract Strict pollution norms make car’s manufacturers to promote electrical and hybrid vehicles (EVs and HEVs). Recuperation system that can capture about 8-25% of the energy is represented by the regenerative brakes, it converts losses of kinetic energy of the car during braking in form of heat to electrical or chemical energy. Regenerative brakes can provide a good increase in car’s autonomy, especially in city driving cycles with high frequency of braking. Also, they reduce friction brakes wear and offer more precisely control of wheel braking torque. A survey in this paper presents basics, uses, types and braking strategies for existing regenerative braking systems with the purpose to identify and detail their limitations. Identifying key factors that have influence on system efficiency allows to elaborate optimizing techniques, strategies and algorithms, applied to existing systems in order to develop future concepts that will overcome current limitations.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution, few combine the connected vehicle technologies into braking velocity planning. If the braking intention is accessed by the vehicle-to-everything communication, the electric vehicles (EVs) could plan the braking velocity for recovering more vehicle kinetic energy. Therefore, this paper presents an energy-optimal braking strategy (EOBS) to improve the energy efficiency of EVs with the consideration of shared braking intention. First, a double-layer control scheme is formulated. In the upper-layer, an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm, which could derive the energy-optimal braking trajectory. In the lower-layer, the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system, then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety. Several simulations are conducted by jointing MATLAB and CarSim, the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy. Finally, the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration, battery charging power, and motor efficiency, which could be a guide to real-time control.

PERFORMANCE EVALUATION OF AN ELECTRIC VEHICLE INTEGRATED WITH REGENERATIVE BRAKING SYSTEM USING PI CONTROLLER

Battery electric vehicles (BEVs) without regenerative braking mechanisms often suffer major drawbacks of limited driving range. Although extensive research works exist in electric vehicles integrated with regenerative braking, the performance evaluation of an electric ambulance, in the context of aerodynamic as well as energy recovery assessment from a complete vehicle modeling perspective based on the difference between the controlled dynamic speed and the drive cycle reference speed is not well reported. To compensate for the problem mentioned above, this paper aims to evaluate the performance of an electric ambulance (EA), integrated with a regenerative braking system (RBS) in comparison to an EA without a regenerative braking system (No RBS), in terms of aerodynamic drag coefficient values, state of charge (SOC), endurance efficiency, statistical correlation and mean absolute error (MAE) using proportional-integral (PI) controller. The SOLIDWORKS and SOLIDWORKS Flow Simulator were used to develop the EA CAD model and conduct aerodynamic analysis. MATLAB Simulink was used to model the EA complete EA system. The EA drive system was evaluated using three drive cycles (UDDS, FTP, and US06). The EA had an aerodynamic coefficient of 0.29. From the perspective of energy recycling, the EV-RBS yielded an extended drive range and appreciable gain in state of charge compared to EV-No RBS on the mentioned drive cycles. Generally, as the deceleration frequency increases from one drive cycle to another, the energy recycling increases, and the range increases correspondingly. In addition, the PI controller, which relied on speed error as a means of regulating the controlled speed, was found to be efficient, as the controlled speed was highly correlated to the reference speed. Overall, very low mean absolute errors in the vehicle speed were observed for the drive cycles considered.

Research on Pressure Control Algorithm of Regenerative Braking System for Highly Automated Driving Vehicles

Conclusive evidence has demonstrated the critical importance of highly automated driving systems and regenerative braking systems in improving driving safety and economy. However, the traditional regenerative braking system cannot be applied to highly automated driving vehicles. Therefore, this paper proposes a fully decoupled regenerative braking system for highly automated driving vehicles, which has two working modes: conventional braking and redundant braking. Aimed at the above two working modes, this paper respectively proposes the pressure control algorithm, based on P-V characteristics, and the pressure control algorithm, based on the overflow characteristics of the solenoid valve. AMESim is utilized as the simulation platform, and then is co-simulated with MATLAB/Simulink, which is embedded with the control algorithm. The simulation results show the feasibility and effectiveness of the regenerative braking system and the pressure control algorithm.

Novel regenerative braking method for transient torsional oscillation suppression of planetary-gear electrical powertrain

Electric regenerative braking systems have drawn much attention in the trends of energy-saving and emission-reduction requirements for electric vehicles. However, the significant differences between regenerative braking transmission chains and the traditional ones have lead to increasing oscillation and noise of electrical powertrain. With the application of planetary-gear transmission chains, adopting an advanced regenerative braking method becomes practical. This paper develops a novel regenerative braking method for transient torsional oscillation suppression of planetary-gear electrical powertrain (PGEP), which uses an angle-varying mesh stiffness-considered transmission model and a genetic algorithm-based method for allocation of electric regenerative braking torque. Simulations are conducted with various angle-varying mesh stiffness and backlash to compare the transient torsional oscillation-suppression performance of PGEP during regenerative braking transition process. For an initial speed of 80 km/h, simulation results show that the proposed torsional oscillation-considered electric regenerative braking torque allocating method performs the best comparing with the traditional methods, which has a 55% reduction in vehicle jerk and 36% improvement in torsional oscillation of PGEP. The AVL experiment results also demonstrated that torsional oscillation-considered regenerative braking method has considerable benefits in both transient torsional oscillation suppression of PGEP as well as enhancement of driving comfort.

Optimalisasi Pengereman Regeneratif dengan Perubahan Sudut Eksitasi pada Pulsa Tunggal

Most of the energy is wasted into heat energy due to conventional braking, so an optimal braking strategy is needed. A Regenerative braking utilizes the kinetic energy of the engine into electrical energy by changing the function of an electric machine into a generator. The regenerative braking system uses a Switched Reluctance Machine (SRM) which has several advantages; simple construction, does not require maintenance, and return energy to the battery. The method that can be used in the regenerative braking system of the SRM is the change of excitation angle to produce the maximum peak phase current. This study aims to optimize regenerative braking by changing the angle (θeks) using simple controls to produce energy that is greater than the battery voltage so that current may flow to the battery when braking occurs. The results of the analysis for method implementation were proven by testing the devices in the laboratory.  Based on the results of the tests, the exact angle was obtained, namely the value of θeks = 20º and the value of θkom = 170º with an initial speed of 1822 RPM, reduced into 1522 RPM by braking process, which could produce a peak current of 12,5 A and a current flowing to the battery was 5A.

HIL Simulation of a Tram Regenerative Braking System

Regenerative braking systems are an efficient way to increase the energy efficiency of electric rail vehicles. During the development phase, testing of a regenerative braking system in an electric vehicle is costly and potentially dangerous. For this reason, Hardware-In-the-Loop (HIL) simulation is a useful technique to conduct the system’s testing in real time where the physical parts of the system are replaced by simulation models. This paper presents a HIL simulation of a tram regenerative braking system performed on a scaled model. First, offline simulations are performed using a measured speed profile in order to validate the tram, supercapacitor, and power grid model, as well as the energy control algorithm. The results are then verified in the real-time HIL simulation in which the tram and power grid are emulated using a three-phase converter and LiFePO4 batteries. The energy flow control algorithm controls a three-phase converter which enables the control of energy flow within the regenerative braking system. The results validate the simulated regenerative braking system, making it applicable for implementation in a tram vehicle.

Personalization of Electric Vehicle Accelerating Behavior Based on Motor Torque Adjustment to Improve Individual Driving Satisfaction.

As worldwide vehicle CO2 emission regulations have been becoming more stringent, electric vehicles are regarded as one of the main development trends for the future automotive industry. Compared to conventional internal combustion engines, electric vehicles can generate a wider variety of longitudinal behaviors based on their high-performance motors and regenerative braking systems. The longitudinal behavior of a vehicle affects the driver’s driving satisfaction. Notably, each driver has their own driving style and as such demands a different performance for the vehicle. Therefore, personalization studies have been conducted in attempts to reduce the individual driving heterogeneity and thus improve driving satisfaction. In this respect, this paper first investigates a quantitative characterization of individual driving styles and then proposes a personalization algorithm of accelerating behavior of electric vehicles. The quantitative characterization determines the statistical expected value of the personal accelerating features. The accelerating features include physical values that can express acceleration behaviors and display different tendencies depending on the driving style. The quantified features are applied to calculate the correction factors for the target torque of the traction motor controller of electric vehicles. This driver-specific correction provides satisfactory propulsion performance for each driver. The proposed algorithm was validated through simulations. The results show that the proposed motor torque adjustment can reproduce different acceleration behaviors for an identical accelerator pedal input.

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.

Retraction: Kwon et al. Cooperative Control Algorithm for Friction and Regenerative Braking Systems Considering Temperature Characteristics. World Electr. Veh. J. 2015, 7, 287–298

The journal retracts the article, ”Cooperative control algorithm for friction and regenerative braking systems considering temperature characteristics” [...]