Braking Of Electric Vehicle Research Articles

Research on Direct-Drive Brake Actuator and Its Control Method for Electric Vehicles

<div>With the rapid development of electric vehicles, the need for improved reliability and safety performance of electric vehicle braking systems has become paramount. In response to this demand, a novel direct-drive brake-by-wire actuator based on linear motors was designed to address these challenges. This article presents the structure and principles of the proposed braking actuator. Leveraging the traditional electromechanical brake systems as a foundation, the prototype was modified and fabricated. Additionally, the control and drive system for the braking actuator was established using the TMS320F28335 digital signal processor. Moreover, the current-position dual closed-loop control algorithm was devised to regulate the braking force accurately. Experimental results demonstrate that the direct-drive brake-by-wire actuator exhibits rapid responsiveness and precise braking force modulation, showcasing promising prospects in the field of electric vehicle braking.</div>

Intelligent Robust Controllers Applied to an Auxiliary Energy System for Electric Vehicles

This paper presents two intelligent robust control strategies applied to manage the dynamics of a DC-DC bidirectional buck–boost converter, which is used in conjunction with a supercapacitor as an auxiliary energy system (AES) for regenerative braking in electric vehicles. The Neural Inverse Optimal Controller (NIOC) and the Neural Sliding Mode Controller (NSMC) utilize identifiers based on Recurrent High-Order Neural Networks (RHONNs) trained with the Extended Kalman Filter (EKF) to track voltage and current references from the converter circuit. Additionally, a driving cycle test tailored specifically for typical urban driving in electric vehicles (EVs) is implemented to validate the efficacy of the proposed controller and energy improvement strategy. The proposed NSMC and NIOC are compared with a PI controller; furthermore, an induction motor and its corresponding three-phase inverter are incorporated into the EV control scheme which is implemented in Matlab/Simulink using the “Simscape Electrical” toolbox. The Mean Squared Error (MSE) is computed to validate the performance of the neural controllers. Additionally, the improvement in the State of Charge (SOC) for an electric vehicle battery through the control of buck–boost converter dynamics is addressed. Finally, several robustness tests against parameter changes in the converter are conducted, along with their corresponding performance indices.

Thermodynamics-Based Energy Management Strategy for Electric Vehicle Braking

Thermodynamics-Based Energy Management Strategy for Electric Vehicle Braking

A Multi-Source Braking Force Control Method for Electric Vehicles Considering Energy Economy

Advancements in electric vehicle technology have promoted the development trend of smart and low-carbon environmental protection. The design and optimization of electric vehicle braking systems faces multiple challenges, including the reasonable allocation and control of braking torque to improve energy economy and braking performance. In this paper, a multi-source braking force system and its control strategy are proposed with the aim of enhancing braking strength, safety, and energy economy during the braking process. Firstly, an ENMPC (explicit nonlinear model predictive control)-based braking force control strategy is proposed to replace the traditional ABS strategy in order to improve braking strength and safety while providing a foundation for the participation of the drive motor in ABS (anti-lock braking system) regulation. Secondly, a grey wolf algorithm is used to rationally allocate mechanical and electrical braking forces, with power consumption as the fitness function, to obtain the optimal allocation method and provide potential for EMB (electro–mechanical brake) optimization. Finally, simulation tests verify that the proposed method can improve braking strength, safety, and energy economy for different road conditions, and compared to other methods, it shows good performance.

Fuzzy Logic-Based Energy Management System for Regenerative Braking of Electric Vehicles with Hybrid Energy Storage System

Electric vehicles (EVs), which are environmentally friendly, have been used to minimize the global warming caused by fossil fuels used in vehicles and increasing fuel prices due to the decrease in fossil resources. Considering that the energy used in EVs is obtained from fossil resources, it is also important to store and use energy efficiently in EVs. In this context, recovery from a regenerative braking system plays an important role in EV energy efficiency. This paper presents a fuzzy logic-based hybrid storage technique consisting of a supercapacitor (SC) and battery for efficient and safe storage of a regenerative braking system. First, the constraints of the battery to be used in the EV for fuzzy logic control are identified. Then, the fuzzy logic system is created and tested in the ADVISOR and Siemens Simcenter Flomaster programs in the New European Driving Cycle (NEDC) driving cycle. A SC was selected for primary storage to prevent the battery from being continuously charged from regenerative braking, thus reducing its lifetime. In cases where the vehicle consumes more energy than the average energy consumption, energy consumption from the battery is reduced by using the energy stored in the SC, and the SC energy is discharged, making preparations for the energy that will come from the next regenerative braking. Thus, the high current values transferred to the battery during regenerative braking are effectively limited by the SC. In this study, the current values on the battery in the EV with a hybrid storage system decreased by 29.1% in the ADVISOR program and 28.7% in the Simcenter Flomaster program. In addition, the battery generated 46.84% less heat in the hybrid storage system. Thus, the heating and capacity losses caused by this current on the battery were minimized. The presented method provides more efficient energy management for EVs and plays an important role in maintaining battery health.

Regenerative Braking in Electric Vehicles using BLDC motor with Modified Torque and Adaptive-Neuro-Fuzzy-Control

Regenerative Braking in Electric Vehicles using BLDC motor with Modified Torque and Adaptive-Neuro-Fuzzy-Control

Improved Energy Management of Capacitive Energy Storage in Metro Railcar by Simulation

This paper focuses on the use of modeling and simulation of a renewable energy. The capacitive energy storages contribute to the rapid energy recovery associated with regenerative braking in electric vehicles. This power system allows the acceleration and deceleration of the vehicle with a lower loss of energy. Short-distance passenger traffic on electrified lines is a domain where brake energy recuperation might reduce the total energy consumption significantly. In this paper the results of simulation models by Matlab-Simulink for an urban-metro railcar and some methods for reducing the needed value of capacitance by an improved energy management are presented. The aim of the new management of the energy storage system for decreasing the needed value of capacitance and improving the system performance is presented.

New Advancement of Supercapacitors Technology: a review

Supercapacitors are exciting for researchers due to their ability to store energy very quickly. This makes supercapacitors ideal for applications requiring rapid bursts of power, like regenerative braking in electric vehicles or short-term backup power for electronics. This makes them ideal for low-power devices we wear or carry around (like phones and smartwatches) and even powerful military equipment (like missiles and torpedoes). Scientists are figuring out how to improve SCs by tinkering with the materials they are made from and how those materials interact. These efforts are being done to make SCs a better option than other ways of storing energy, like rechargeable batteries. This article explores the latest findings on how SCs store energy, the materials used to make their electrodes (especially 3D structures that look like paper or fibers), and how they are being used in the real world.

Method of electric vehicle braking energy recovery

Currently, the issue of the use of network power storage devices is increasingly being discussed. A promising technical solution is to combine a flywheel and a motor-generator motor on one shaft. Such an association can be called electromachine energy accumulators. Its main disadvantage should be considered the management difficulties. In this regard, it is possible to use an energy recovery system to reduce energy consumption and increase stability in the power grid. Such devices can reduce energy costs and increase the efficiency of vehicles. Such a solution can be useful and effective for the development of electric transport and reducing energy costs.

Estimating the effectiveness of electric vehicles braking when determining the circumstances of a traffic accident

In the vast majority of cases, the braking process is used to prevent traffic accidents. The effectiveness of this process depends on the design and functionality of vehicle braking systems (presence of anti-lock braking system, emergency braking system, preventive safety systems, etc.) and is limited by the amount of frictional forces in contact of tires with the road. The improvement of methodical approaches to evaluating the effectiveness of braking of cars contributes to increasing the accuracy and objectivity of establishing the circumstances of the occurrence of emergency situations. The paper analyses existing methods of evaluating the braking parameters of vehicles (including those with an electric drive) and modern methods of evaluating electric vehicle braking parameters and conducting auto-technical investigations of traffic accidents, which relate to using different methodological approaches and digital technologies at all stages of expert research. In contrast to existing models, the proposed mathematical model for estimating the trajectory of two-axle cars during braking allows for considering various types of input parameter uncertainty, reducing the range of possible modeling errors by 39%. Comparing simulation results and experimental data showed that the average relative error is 4.58%, and the maximum error did not exceed 7.82%. The performed study of the stability of the electric vehicles' movement during emergency braking with the help of developed mathematical models in the Mathcad software environment reveals the content of the algorithm of a similar calculation in specialized computer programs of auto technical examination. Conducting such calculations is relevant in the analysis of real accident situations, where specific circumstances and features that cannot be considered during modeling in specialized software must be taken into account. Simultaneously, the probability of type I errors is reduced by 2–19%, and type II errors are reduced by 43–68%.

Regenerative Braking of Electric Vehicles Based on Fuzzy Control Strategy

Regenerative braking technology is a viable solution for mitigating the energy consumption of electric vehicles. Constructing a distribution strategy for regenerative braking force will directly affect the energy saving efficiency of electric vehicles, which is a technical bottleneck of battery-powered electric vehicles. The distribution strategy of the front- and rear-axle braking forces of electric vehicles that possess integrated front-wheel-drive arrangements is established based on the Economic Commission of Europe (ECE) regulations, which enables the clarification of the total braking force of the front axle. The regenerative braking torque model of the motor is adjusted to optimize the ratio of motor braking force to the whole front-axle braking force. The regenerative braking process of electric vehicles is influenced by many factors, such as driving speed and braking intensity, so regenerative braking presents characteristics of nonlinearity, time variability, delay, and incomplete models. By considering the impact of fuzzy controllers having better robustness, adaptability, and fault tolerance, a fuzzy control strategy is employed in this paper to accomplish the regenerative braking force distribution on the front axle. A regenerative braking model is created on the Simulink platform using the braking force distribution indicated above, and experiments are run under six specific operating conditions: New European Driving Cycle (NEDC), World Light-Duty Vehicle Test Cycle (WLTC), Federal Test Procedure 72 (FTP-72), Federal Test Procedure 75 (FTP-75), China Light-Duty Vehicle Test Cycle-Passenger (CLTC-P), and New York City Cycle (NYCC). The findings demonstrate that in six typical cycling road conditions, the energy saving efficiency of electric vehicles has greatly increased, reaching over 15%. The energy saving efficiency during the WLTC driving condition reaches 25%, and it rises to 30% under the FTP-72, FTP-75, and CLTC-P driving conditions. Furthermore, under the NYCC road conditions, the energy saving efficiency exceeded 40%. Therefore, our results verify the effectiveness of the regenerative braking control strategy proposed in this paper.

Research on Electric Vehicle Braking Intention Recognition Based on Sample Entropy and Probabilistic Neural Network

The accurate identification of a driver’s braking intention is crucial to the formulation of regenerative braking control strategies for electric vehicles. In this paper, a braking intention recognition model based on the sample entropy of the braking signal and a probabilistic neural network (PNN) is proposed to achieve the accurate recognition of different braking intentions. Firstly, the brake pedal travel signal is decomposed to extract the effective components via variational modal decomposition (VMD); then, the features of the decomposed signal are extracted using sample entropy to obtain the multidimensional feature vector of the braking signal; finally, the sparrow search algorithm (SSA) and probabilistic neural network are combined to optimize the smoothing factor with the sparrow search algorithm and the cross-entropy loss function as the fitness function to establish a braking intention recognition model. The experimental validation results show that combining the sample entropy features of the braking signal with the probabilistic neural network can effectively identify the braking intention, and the SSA-PNN algorithm has higher recognition accuracy compared with the traditional machine learning algorithm.

Development of a method for regenerative braking of an electric scooter

<span lang="EN-US">In this work, a method of regenerative braking of an electric scooter was developed. Regenerative braking of electric vehicles is the basis for energy saving cars and environmental protection. A stand was made for the study of a magnets and an ionistor. In the proposed method, an ionistor is additionally connected in parallel to the battery, which charges faster than the battery, so the process of accelerating the electric vehicle after stopping also occurs faster. It should also be noted that if emergency braking is necessary to stop an electric vehicle, the driver can press the brake pedal and stop the car using brake pads. The paper investigates the method of the element base for the vehicle, as well as control. To develop this study, an electric scooter was chosen as an electric vehicle model. The dependences of the electric current on the operating time of the ionistor in three positions are determined. During the actual speed of the electric scooter corresponds to the controlled speed.</span>

Study on multi-closed loop control of electro-mechanical braking for electric vehicles based on clamping force

In order to improve the clamping force control accuracy of electro-mechanical braking system of electric vehicles, a multi-closed loop control strategy of electro-mechanical braking based on clamping force is proposed. A detailed EMB mathematical model is established. The sliding mode speed controller and improved fuzzy PID clamping force controller are designed, and the joint simulation model of the speed the clamping force controller is established, and simulation experiments are used to verify the effectiveness of the control strategy. Comparative analysis of three simulation conditions, the maximum adjustment time of the proposed control strategy is 0.254 s and the maximum overshoot is 0.45%. The results of research show that the control strategy designed in this paper can quickly and stably reach the target value of clamping force, has a strong anti-interference capability, has some reference value in the electric vehicle braking control.

Design and analysis of reconfigurable sensorless brushless DC motor drive for regenerative braking and battery charging in electric vehicle

SummaryThe expected depletion of fossil fuels has brought in an increased demand for electric vehicles with better performance in terms of easiness of control and reliability of operation and hence is a fertile area of research. In the present scenario, motoring, regenerative braking, and charging operations are performed in electric vehicles by separate converters. In this paper, an integrated scheme is developed, wherein the same voltage source inverter is employed to obtain all the three modes of operation, which in turn reduces the number of switching devices. Further, a sensorless control used in the proposed scheme improves the operational reliability. This novel approach adopts a simple switching scheme for voltage source inverter to operate as a dual‐boost DC‐DC converter during the regenerative braking period. This switching scheme enables reconfiguring voltage source inverter to a dual‐boost rectifier in conjunction with a LLC resonant converter in the charging mode. A comparison is also provided between the performance of single switch boost and dual‐boost converters used for braking operation. The performance of a prototype brushless DC (BLDC) motor drive with Li‐ion battery pack is evaluated in motoring, regenerative braking, and battery charging modes. This paper presents a detailed design of the scheme, the simulation of which is done on a MATLAB/SIMULINK platform and validated experimentally.

Sound Generation by Metro Trains during Braking and Its Suppression Method

The causes of acoustic noise occurring during braking of electric vehicles, in particular, in the metro, were analyzed. The spectrum of such noise was measured, and it is shown that high-frequency discrete tones are excited by braking resistors, applied for electrodynamic braking of electric vehicles. Three proposed mechanisms of electromechanical interaction in a Fecral plate, which is a braking resistor element, were considered: the Ampère force and linear and nonlinear magnetostriction. It was shown that predominant odd harmonics indicate the presence of a significant piezomagnetic effect and the inverse effect of linear magnetostriction in the Fecral alloy. A phenomenological approach was used to calculate the piezomagnetic tensor elements for Fecral. Calculations by the finite element method showed that asymmetric cuts introduced into the plate may significantly decrease intensity of acoustic vibrations excited by the braking resistor.

Regenerative braking torque compensation control based on improved ADRC

Electro-hydraulic braking (EHB) compensation is an effective method to solve the insufficient regenerative braking of electric vehicles, but the accuracy and speed of executive pressure response are still insufficient. In order to solve this problem, a brake pressure compensation control method based on EHB system is proposed and verified. Firstly, adaptive LuGre friction model and braking dead time compensation are introduced to obtain a more accurate friction model. Then, an electro-hydraulic braking control strategy based on Improved Active Disturbance Rejection Control (IADRC) is proposed. Finally, the effectiveness of the proposed method is verified by simulation experiments and hardware-in-the-loop (HIL) simulation experiments. The test results show that the proposed control method can achieve accurate control of brake pressure compensation in time. The research results promote the research and application of EHB system to a certain extent.

Autonomous Emergency Braking of Electric Vehicles With High Robustness to Cyber-Physical Uncertainties for Enhanced Braking Stability

Modern autonomous emergency braking (AEB) system is a typical safety-critical cyber-physical system (CPS) synthesizing the vehicular communications, control, and proception technologies. However, the control performance of braking can be easily deteriorated by the road adhesion saturation in physical environment and the multi-hop communication network-induced delays in cyber systems. Motivated by this, a new multi-hop loop delay analysis method and its associated upper-bound expression is proposed to scrutinize the system uncertainties, within the scope of CPS. Following this endeavor, a hierarchical cyber-physical control scheme for the AEB system is proposed to mitigate the adverse effects of road adhesion saturation and multi-hop communication network-induced delays. At the upper layer, a μ-adaptive time-to-collision (TTC) planning strategy is adopted to generate the desired acceleration for collision risk avoidance considering the road adhesion saturation. At the lower layer, an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> -based linear quadratic regulator (LQR) is designed for acceleration tracking with strong robustness to the uncertainties of cyber system. Hardware-In-Loop (HIL) experiments validate that the proposed method is superior in terms of braking accuracy and the robustness to the system uncertainties.

Axial Unipolar Eddy Current Brake Performance Characteristics Against Heat Increase in Rotor

The development of transportation technology in the automotive sector such as electric vehicles is increasingly advanced. One technology that is needed quite a lot is the development of supporting technology for electric vehicle braking. The use of regenerative braking on light electric vehicles such as 2-wheeled vehicles is not efficient because of its low weight. The use of Eddy Current Brake (ECB) can be a solution for braking support needs. This is because the ECB is a braking system that has the advantage of a lightweight design but still relies on the frictionless principle. However, in addition to its advantages, the eddy current brake is still in the early stages of its research with efficiency that still needs to be developed. In the discussion of the ECB, heat generation is one of the interesting topics to be discussed. Specifically, the study of the characteristics of the unipolar ECB axial performance on heat generation events has not yet been discussed. So this article aims to discuss these events with a simulation process and simple mathematical calculations. Design optimization is done to get the best value. As a result, the use of eddy current brakes with conductor disks using slots, can improve the performance of the ECB on the torque side and cooling side. Thus, this article is a good contribution to the sustainability of ECB research in both the general and automotive fields.

Research on ABS control strategy of cornering braking of electric vehicle with four in-wheel-motors

Research on ABS control strategy of cornering braking of electric vehicle with four in-wheel-motors