Control System For Electric Vehicle Research Articles

Electric Vehicle Control System by using Controller Area Network Communication

The Controller Area Network (CAN) communication protocol is designed by Bosch in the 1980s as a doubled wired, differential voltage-based serial communication system for control systems. Electric vehicles, like Gasoline vehicles, require controllers to regulate load operation, where conventional point-to-point communication system gets outcome of huge number of cables in the harness. CAN is used to minimize the amount of cables and enable various controllers to transfer data and accomplish complicated jobs simultaneously. This paper presents the design of a CAN-based control system to be used as a replacement for the existing system and shows the development of four modules as well as a proposed implementation for the complete system. Individual modules will be developed initially and later interfaced to the CAN network with CAN controller modules. All modules are connected with a twisted pair of cables for data transmission with CAN.

Control system for unmanned transport electric vehicles based on microwave Doppler sensors

Control system for unmanned transport electric vehicles based on microwave Doppler sensors

Modelling of Electric Vehicle with PID Controller Transfer Function using GA and Model-Reduced Order DRA Algorithm

In this paper, a model of an electric vehicle transfer function using GA and a model-reduced order discrete time realization (DRA) algorithm is presented. The electric vehicle (EV) control system regulates vehicle speed according to the driver’s command signal and brings the vehicle to its equilibrium point, i.e., the desired speed under any abnormal conditions. The controller transfer function is designed based on EV's dynamic differential equations. An infinite-order transcendental transfer function for the EV model is approximated to find high-reliability discrete-time state-space reduced-order models (ROMs). Reduced the robustness and increased the predictions' accuracy of ROM output in terms of accurate numerical simulations of the EV transfer function. Also, the design of the PID controller parameter using optimization techniques (OT) for the tuning of conventional controllers for the desired speed is done using a linearized model. In this study, the performance of a conventional PID controller is compared with that of a GA-based PID controller. In terms of maximum overshoot, peak time, rising time, settling time, and steady state error, the simulation results show that the suggested controller is preferable.

Regen-braking-capable ZF Brake Control System for Electric Vehicles by VW

Regen-braking-capable ZF Brake Control System for Electric Vehicles by VW

Hierarchical speed control for autonomous electric vehicle through deep reinforcement learning and robust control

For the speed control system of autonomous electric vehicle (AEV), challenge happens with how to determine an appropriate driving speed to satisfy the dynamic environment while resisting uncertainty and disturbance. Therefore, this paper proposes a robust optimal speed control approach based on hierarchical architecture for AEV through combining deep reinforcement learning (DRL) and robust control. In decision-making layer, a deep maximum entropy proximal policy optimization (DMEPPO) algorithm is presented to obtain an optimal speed via dynamic environment information, heuristic target entropy and adaptive entropy constraint. In motion control layer, to track the learned optimal speed while resisting uncertainty and disturbance, a robust speed controller is designed by the linear matrix inequality (LMI). Finally, simulation experiment results show that the proposed robust optimal speed control scheme based on hierarchical architecture for AEV is feasible and effective.

Research on Decoupled Optimal Control of Straight-Line Driving Stability of Electric Vehicles Driven by Four-Wheel Hub Motors

The optimal control strategy for the decoupling of drive torque is proposed for the problems of runaway and driving stability in straight-line driving of electric vehicles driven by four-wheel hub motors. The strategy uses a hierarchical control logic, with the upper control logic layer being responsible for additional transverse moment calculation and driving anti-slip control; the middle control logic layer is responsible for the spatial motion decoupling for the underlying coordinated distribution of the four-wheel drive torque, on the basis of which the drive anti-skid control of a wheel motor-driven electric vehicle that takes into account the transverse motion of the whole vehicle is realized; the lower control logic layer is responsible for the optimal distribution of the driving torque of the vehicle speed following control. Based on the vehicle dynamics software Carsim2019.0 and MATLAB/Simulink, a simulation model of a four-wheel hub motor-driven electric vehicle control system was built and simulated under typical operating conditions such as high coefficient of adhesion, low coefficient of adhesion and opposing road surfaces. The research shows that the wheel motor drive has the ability to control the stability of the whole vehicle with large intensity that the conventional half-axle drive does not have. Using the proposed joint decoupling control of the transverse pendulum motion and slip rate as well as the optimal distribution of the drive force with speed following, the transverse pendulum angular speed and slip rate can be effectively controlled with the premise of ensuring the vehicle speed, thus greatly improving the straight-line driving stability of the vehicle.

Longitudinal Motion Control of Electric Vehicles: Glocal Model and Design Using Passivity

This article presents a framework to model and design the longitudinal motion control (LMC) system for electric vehicles (EVs). Thanks to the passivity property of EVs, a hierarchical control configuration including three layers is proposed. In the lower layer, each actuator is provided a disturbance observer (DOB) for locally preventing the wheel slip. A global controller is designed in the upper layer for the cruising purpose. In addition, the middle layer serves as the aggregation and distribution channels.

A pulse‐and‐glide ‐driven adaptive cruise control system for electric vehicle

As the adaptive cruise control system (ACCS) on vehicles is well-developed today, vehicle manufacturers have increasingly employed this technology in new-generation intelligent vehicles. Pulse-and-glide (PnG) strategy is an efficacious driving strategy to diminish fuel consumption in traditional oil-fueled vehicles. However, current studies rarely focus on the verification of the energy-saving effect of PnG on an electric vehicle (EV) and embedding PnG in ACCS. This paper proposes a pulse-and-glide-driven adaptive cruise control system (PGACCS) model which leverages PnG strategy as a parallel function with cruise control (CC) and verifies that PnG is an efficacious energy-saving strategy on EV by optimizing the energy cost of the PnG operation using Intelligent Genetic Algorithm and Particle Swarm Optimization (IGPSO). This paper builds up a simulation model of an EV with regenerative braking and ACCS based on which the performance of PGACCS and regenerative braking is evaluated; the PnG energy performance is optimized and the effect of regenerative braking on PnG energy performance is evaluated. As a result of PnG optimization, the PnG operation in the PGACCS could cut down 28.3% energy cost of the EV compared to the CC operation in the traditional ACCS which verifies that PnG is an effective energy-saving strategy for EV and PGACCS is a promising option for EV.

Research on Control Strategy and Central Control System of Intelligent Electric Vehicle

With the continuous improvement of world science and technology, vehicle technology has also been greatly developed. Cars bring convenience to people’s travel, and occupy an increasingly high proportion in social life. Automobile plays an important role in the continuous progress of contemporary society and the change of human travel conditions. At the same time, the increasing number of cars also brings many problems: energy consumption and environmental pollution are worsening, traffic accidents are increasing year by year. According to the who survey, the number of casualties caused by traffic accidents in China is gradually increasing. High traffic accidents have caused irreversible losses to social development, people’s lives and property. It has become the development goal to improve the vehicle active safety, control the vehicle to automatically identify the road, drive according to the planned route and reduce the frequency of traffic accidents. In the traditional driving environment, people occupy a dominant position. In the face of complex and changeable traffic environment and a large number of traffic information, it is easy to make mistakes in driving and cause serious traffic accidents. Therefore, it is very important to extricate the driver from the complex and changeable traffic environment and make driving safer. The intelligent vehicle collects the information about the road and the vehicle itself through the sensor, and sends it to the central controller which controls the transverse and longitudinal movement of the electric vehicle. The central controller sends out corresponding instructions to control the horizontal and longitudinal operation of the vehicle according to the control strategy, so as to realize the control of the driving behavior of the vehicle, so that the vehicle can drive safely on the desired track at the expected speed, It can avoid driver fatigue driving behavior and traffic accidents caused by driving technology. Various sensors in the intelligent vehicle can obtain more vehicle information at the same time, and control the vehicle through the controller processing.

Optimization and Enhancement of Charging Control System of Electric Vehicle Using MATLAB SIMULINK

Several algorithms and approaches have been adopted for wide range of controlled systems. One of the most interesting algorithms was the Rider Optimization Algorithm (ROA), which has been widely used in many applications for the control system. In this paper, the ROA algorithm has been utilized in the Controlled System (Charging Control System associated and decrease the steady-state error, high overshoot, decreasing for rising time and settling time these issues that we are looking for disentangling it in the controlled System to get furthest reaches of depending capacity that makes Controller work in a best case. of Electric Vehicle) to enhance and optimize the charging procedure. Results obtained shows significant enhancement where the parameter values achieved for the Maximum overshooting, raising time, peak time and the settling time were zero%, 0.0341, 0.7, 0.1188 second respectively, which could be considered as more realistic results as compared with latest work in the same field. Such results have showed a significant enhancement as compared to the related results achieved in the same manner.

An Overview of IoT-Enabled Monitoring and Control Systems for Electric Vehicles

As 5G technology becomes operational and continues to expand, smart cities become a reality that is transforming urban life at a rapid pace. Electric Vehicles (EV) and automated driving, equipped with Battery Energy Storage Systems (BESSs), are expected to dominate public transportation in smart cities. While new technologies can facilitate efficiency and reduce the costs in a city, they can also present challenges. This paper provides an overview of the technical challenges of real-time monitoring and control of Energy Storage Systems (ESSs) for EVs in smart cities. It also covers the Internet-of-the-Things (IoT) technology that can be utilized to address the challenges and improve the efficiency of Battery Management Systems (BMS). Autonomous Wireless Sensor Networks (WSNs) in smart cities provide the infrastructure to support advanced EV features, such as self-parking. IoT sensors can also be used to determine the State-of-Charge (SoC) in EVs by data-driven methods and cloud computing services.

Microcomputer Energy Saving Control System for Electric Vehicles Under Artificial Intelligence

Faced with the problem of dwindling oil resources and increasingly strict automobile exhaust emission standards, the advantages of pure electric vehicles in energy saving and emission reduction have become more and more prominent compared with traditional fuel vehicles. However, in view of the current development scale of the pure electric vehicle market, there are still many deficiencies in the aspects of power density, cycle service life and replacement cost. This paper mainly studies the microcomputer energy saving control system of electric vehicle under the background of artificial intelligence. In this paper, the STM32F103 series chip is used as the main control chip of the battery energy management system. Then according to the requirements of the subject of each module circuit design, forming a complete battery energy management system circuit design. In this paper, the designed electric vehicle energy management system has been tested. The test results show that the electric vehicle battery energy management system has perfect function, sTable operation, and can realize the energy management of electric vehicle battery pack. It can accurately predict the state of charge of electric vehicle lithium battery, and effectively improve the battery performance of electric vehicle lithium battery, and achieve the effect of energy saving.

Intelligent control system for high efficiency Electric Vehicles

Brush-less Direct Current (BLDC) motor drive systems are widely used in electric vehicles (EV). However, most EV control strategies only focus on BLDC motors without considering changes in different driving conditions. This paper proposes an intelligent control strategy based on an intelligent neural network that can change control parameters based on changing driving conditions. This system has the ability to self-learning and adapt based on driving conditions. The simulation is carried out using the Electric Vehicle Drive Train model and run on the MATLAB-SIMULINK platform. The simulation results show that the smart control strategy designed shows very good efficiency with minimal errors and quickly adapts to different driving conditions.

Повышение безопасности внутризаводского и служебного автомобильного и электротранспорта путем внедрения современных цифровых устройств

Introduction. Industrial injuries are one of the most pressing problems in the field of occupational safety at enterprises of the main industries in the Russian Federation. Most cases of such injuries are noted when moving goods and people by means of various types of interfactory transport. A set of regulatory documents developed in recent years by the Government of the country is dedicated to solving this problem. In accordance with the current trends in the development of new technical solutions, the use of a complex of devices based on IT-technologies is effective. This article is devoted to improving the safety of interfactory and company motor and electric vehicles by introducing modern digital devices. Problem Statement. Almost all large industrial enterprises have a need to move goods and personnel both to the place of production activities and within the enterprises. Motor and electric vehicles used for these purposes do not always undergo a maintenance check, they often undergo technical inspection and repairs with whatever funds remains, and always the personnel operating these vehicles do not have permission to drive. Possible accidents with interfactory and company vehicles occurring as a result of insufficient control over the technical condition of vehicles and inadequate or absent medical and administrative checks of the operating personnel can lead to injuries at the enterprise. Theoretical Part. This article proposes methods for reducing traffic accidents of interfactory and company motor and electric vehicles of industrial enterprises and warehouse enterprises through the introduction of remote monitoring of operation based on IT-technologies, operating with the use of mobile applications that use Internet of Things technologies. The options for introducing security elements designed to reduce the number of transport accidents in internal transport of industrial enterprises and warehouse complexes are considered. An experiment was carried out to introduce system components to vehicles of an industrial enterprise. Conclusion. The use of the proposed monitoring and control system for motor and electric vehicles at machine-building enterprises and warehouse complexes will make it possible to quickly resolve issues related to labor protection, the economy of the enterprise and compliance with the labor discipline. In particular, it is planned to reduce vehicle failures due to mechanical failures, as well as to make timely decisions on the removal from driving the drivers who are not feeling well.

Intelligent speed control system for electric vehicle

An important topic nowadays is to have cars and roads that provide comfort and safety. Mechatronics systems are used to have this approach. The brake system is now base on an electronic stability system, the steering system is partly or fully automated and the speed is control by the cruise control system. The new target for the automotive industry is to create a car able to decide by itself on all actions related to safety and comfort – a fully automated vehicle. One of the most important innovations for autonomous driving is drive by the idea of connected cars: car2car and car2infrastructure. In the present paper, it is analysed a cruise control system based on communication technology. A simple prototype is build up using Arduino and modules for communication. To calibrate and parametrize the system, we use a Simulink model.

A Basic Study on Sound Control System for Ultra-Compact Electric Vehicle by Using Masking

In this study, we conducted a quantitative evaluation of the comfort of the interior of an electric vehicle (EV) using the brain wave appearance rate, which is part of the human biologic information that the initial stage of the proposed active noise control (ANC) system for ultra-compact EVs reveals. EVs have become easy-to-use mobility solutions and have been researched and actively developed focusing on using music characteristics. We performed fundamental testing of music including 1/f fluctuation for the evaluation of ride comfort based on the relationship between the participant’s heart rate and tempo of music using a driving simulator. The results suggest that if a passenger listened to music including a 1/f fluctuation, then he/she could relax. Thus, it was concluded that if we could pre-grasp the passenger’s biologic information of the heart rate and beats per minute for masking, then the comfort in the interior space could be improved even when using a driving simulator.

Sensorless Driving/Braking Control for Electric Vehicles

A sensorless driving/braking control system for electric vehicles is explained in the present paper. In the proposed system, a field-oriented control (FOC) was used to integrate driving and braking controls in a unified module for reducing the cost of hardware and simultaneously incorporating functional flexibility. An antilock braking system can swiftly halt a vehicle during emergency braking. An electromagnetic reverse braking scheme that provided retarding torque to a running wheel was developed. The scheme could switch the state of the MOSFETs used in the system by alternating the duty cycle of pulse width modulation to adjust the braking current generated by the back electromotive force (EMF) of the motor. In addition, because the braking energy required for the electromagnetic braking scheme is related only to the back EMF, the vehicle operator can control the braking force and safely stop an electric vehicle at high speeds. The proposed integrated sensorless driving and electromagnetic braking system was verified experimentally.

Electronic Differential Control of Independent Wheel Drive NEV using Drive Current Balancing Strategy

This paper presents the design and real-time implementation of an electronic differential speed control system (EDSC) for a neighborhood electric vehicle (NEV) with a decentralized power train configuration. The EDSC supervises the desired speed variation of the drive motors of the vehicle at various turning trajectories. The core focus of this design is to reduce the system complexity, computation delay and design expenses with an aid of a newly proposed drive current balancing algorithm (DCBA). The embedded DCBA based EDSC allocates the necessary torque to each wheel solely depending on the motor current variables. Thus, it eliminates the necessities of typical feedback variables-steering and speed to control the EDSC. The developed system performance is being investigated in situ real time on-board experiment. Results in the context of response time, design simplicity and performance reveal the effectiveness of the proposed framework.

Design of Charging Pile Control System for Electric Vehicle Based on BP Neural Network

This paper presents a design scheme of charging pile control system for electric vehicle based on BP neural network and PID control. The design goal of this scheme is to design a charging pile control system for electric vehicles which is suitable for public parking lot and district parking lot. It can realize fast charging of electric vehicles, human-computer interaction with the system, calculation of consumer price and other functions.

Design method considering the frequency band of the disturbance in the DC link voltage control system of hybrid electric vehicle driving systems

AbstractDC link voltage variable systems with DC/DC converter are used in hybrid electric vehicles for improving the power of the system by boosting the DC link voltage. Voltage feedback control using only proportional compensator has been proposed as a control method for the DC/DC converter. The control system can be easily designed, but there is a possibility that a steady‐state error occurs in the DC link voltage. In this paper, a proportional integral compensator is proposed to eliminate the steady‐state error of the DC link voltage in DC link voltage feedback controllers. In addition, when designing the gain of the compensator, the frequency band of the disturbance is considered. The proposed method is verified through experiments on the downsizing model.