Top PDF A microprocessor based control system for an electric vehicle

A microprocessor based control system for an electric vehicle

A microprocessor based control system for an electric vehicle

THE CONTROL INTERFACE The along INPUTS and their outputs lerator motor - analog level system, follows: as voltage bipolar - to proportional temperature - analog to proportional digital -[r]

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Hybrid Sliding Mode Control Technology of Electric Vehicle Based on Wireless Sensor

Hybrid Sliding Mode Control Technology of Electric Vehicle Based on Wireless Sensor

In summary, the working environment of the electric vehicle is complicated, and the system parameters are susceptible to interference. The conventional control algo- rithm is difficult to achieve satisfactory results. In order to realize the accurate com- mutation control, brushless DC motor for traditional electric vehicle needs position sensor to obtain the rotor position information. The current control strategy cannot accurately track the effect of time-varying variables on the control results. The sliding mode control strategy has some disadvantages such as long convergence time and chattering. Therefore, our aim is to solve the existing control strategy long conver- gence time, sliding mode chattering and so on defects. For Sensorless Brushless DC motor control strategy, a modified extended Kalman state correction estimation scheme is proposed, and dual mode high-order non-singular terminal hybrid sliding mode control technology is put forward. TMS320F2812DSP core controller and CM200DY-12H inverter module and construction electric car core control module are established, and the program algorithm of the extended Kalman algorithm and hybrid sliding mode control is constructed.
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Load Frequency Control of a Two Area Power System with Electric Vehicle and PI Controller

Load Frequency Control of a Two Area Power System with Electric Vehicle and PI Controller

The entire interconnected system network is called the Grid. As the increasing environmental and energy security concerns, renewable energy from wind or solar as well as Electric Vehicles (EVs) will be widely deployed in the smart grid in the next decade. The large-scale integration of these new types of generation and load in power grids will have significant impact on grid operation, planning and stability control. The widespread penetration of large scale wind power has been increasing largely because of plentiful availability and reduced CO 2 emissions [1]–[3]. However, the
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Electric Vehicle Regenerative Braking Control Strategy Based on Braking Time Identification

Electric Vehicle Regenerative Braking Control Strategy Based on Braking Time Identification

Get different braking time by the braking force as a function of braking time in figure 7, braking force distribution ratio in vehicle corresponding total required braking force as shown in table 1. It can be seen from table 1 that the braking time is longer, the regenerative braking force ratio to total demand braking force increse, the more braking energy recovery. Regenerative braking force ratio minish with the reduction of braking time, because the braking time shorter braking intensity bigger, the battery can accept the maximum charge current increase is limited, when the motor braking force reaches the maximum value, remaining braking by hydraulic brake to supplement.
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NI Labview based Monitoring and Control of Charging Unit for Hybrid Electric Vehicle

NI Labview based Monitoring and Control of Charging Unit for Hybrid Electric Vehicle

A Battery is a device that can create electricity from the chemical reaction. It converts the MOLECULES inside the battery into electricity. They produce DC supply from the battery. Electricity (electricity that flows of electrons in one direction, and does not switch back). Using the electricity from the battery can provide electricity in areas that do not have electric power distribution. It can be one cell or a group of cells is connected in parallel to reach the required voltage for user application. Each cell has an anode is a positive terminal, a cathode is negative terminal and electrolyte is a substance produce an electrically conducting solution. The electrolyte can be liquid or solid. It is a type of lead-acid and can be dangerous to touch. The chemical reaction of anode reacts with the electrolyte to produce electrons. The cathode reacts with the electrolyte creates the holes and wants electrons. An electric current transferred from happens when a wire connects the anode to the cathode, and the electrons move from one end to the other end. Depending on the type of electrolyte a battery is called a wet cell or dry cell battery. The battery cells can be connected to make a large battery. Connecting the positive terminal of one cell to the negative terminal of the next cell is called connecting them in series. Each battery is connected together are the voltages added together. Four 12 volt batteries connected in series will make 48 volts. Connecting the positive of one cell to the positive terminal of the other, and the negative terminal to the negative is called connecting them in parallel. The voltages are the same cannot be changed, but the current is added together. Voltage is the potential difference to the electrons through the wires, it is measured in volts. Current is a number of electrons are flowing through the wire, it is measured in amps. The multiple of current and voltage is the power (P=VI) of the battery. It is measured in watts.
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Bounds for Optimal Control of a Regional Plug-In Electric Vehicle Charging Station System

Bounds for Optimal Control of a Regional Plug-In Electric Vehicle Charging Station System

ABSTRACT: In order to support the increasing penetration of plug-in electric vehicle (PEV) users, a novel regional PEV charging station system with DC level 3 fast charging is proposed in this project. To promote sustainable development, the proposed system is designed to be equipped with a distributed energy storage system charged by wind generation, solar PV generation, and electricity from the power grid, which can simultaneously charge multiple PEVs. The objective of the proposed system is to minimize operational cost. In practical, power grid is in the need of storage system that must charge/discharge the power during stochastic period of grid. While incorporating the batteries into the power grid, it is required to maintain the best charging coordinates or otherwise it will rise tradeoff between the cost and power delivery. This project is proposed for the purpose of introducing the vehicle battery cost model for the micro grid system to deliver an optimum unit commitment. In this work, the vehicle battery cost model is designed and optimum battery charging/discharging coordinates are effectively done with the help of well-known technique called ‘simulated annealing’ algorithm. With this intelligent control method, it is possible to achieve minimum vehicle battery operating cost and also possible to manage the load variability. The proposed work is implemented on MATLAB R2014a software with the real time data collected for solar and wind power systems. The results are showing the effectiveness of the proposed simulated annealing based battery cost optimization technique.
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Arduino Based Automatic Vehicle Control System

Arduino Based Automatic Vehicle Control System

A Relay control is used to cut the ignition as soon as the vehicle comes to a halt. The functioning of relay and servo motor in our desired way is possible because of the use of the arduino as an interface medium. In the programming of the arduino we have specified for the timing of eye blinking that is after what time if the eye remains close the buzzer will go on, while in the programming it is specified when the relay will be

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Generic model control design for hybrid energy storage system in electric vehicle

Generic model control design for hybrid energy storage system in electric vehicle

The use of energy for different purposes has rapidly increased in the past few decades. The Energy Information Administration (EIA) has recently released data showing that the transportation of people is the main consumer of the energy. As the environmental issues energy consumption and oil crisis arise, new technologies have been developed all around the world to find an alternative and efficient energy source for vehicles. Among all these developments, hybrid electric vehicles have attracted researchers’ and engineers’ attention as an efficient and promising technology for the future. A stand-alone fuel cell system cannot provide an Electric Vehicle (EV) with the required power during sudden changes of load demand; therefore, a supercapacitor (SC) is required to provide the vehicle with the desired peak power during start-up, acceleration, deceleration or sudden external disturbance [1]. This combination of two energy sources, which has been identified as the hybrid energy system, should supply the EV with enough energy to run for larger distances, which eventually results in an increase in the overall efficiency of the vehicle. The energy that is provided by both the fuel cell and SC needs two DC-DC converters to travel through the system.
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CAN Control System for an  Electric Vehicle

CAN Control System for an Electric Vehicle

Until recently, various control systems within a vehicle were completely independent of one another, preventing the chance of sharing information around the vehicle. Sharing information between independent control systems within a vehicle can make the vehicle safer, more reliable and more fuel efficient. Traction control, which is almost a necessity in modern vehicles, is a safety example, where four sensors are employed around the vehicle, each measuring the rotational speed of a wheel and sending the readings to a main control system. The main control system then assesses the information received from all four sensors and determines, by calculating rotational speed differences, whether or not one or more of the wheels has lost traction. If the main controller finds that one of the wheels is spinning faster than the others, it sends a message to the brake control system telling it to apply the brakes to that specific wheel. In doing so, the main controller ensures that the vehicle will always be in contact with the road, thus, providing a safer ride for all passengers onboard.
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A Battery Equalisation System for Electric Vehicle

A Battery Equalisation System for Electric Vehicle

The selected PWM control IC is SG3526 and its block diagram is shown in Figure 3.2. The SG3526 is a high performance monolithic pulse width modulator circuit designed for fixed- frequency switching regulators and other power control applications. Included in the 18-pin dual-in-line package are a temperature compensated voltage reference, sawtooth oscillator, error amplifier, pulse width modulator, and two low impedance power drivers. Also included are protective features such as soft-start and undervoltage lockout, digital current limiting, double pulse inhibit, a data latch for single pulse metering, adjustable deadtime, and provision for symmetry correction inputs. For ease of interface, all digital control ports are TTL and B-series CMOS compatible. Active LOW logic design allows wired-OR connections for maximum flexibility. This versatile device can be used to implement single-ended or push-pull switching regulators of either polarity, both transformerless and transformer coupled. The SG3526 is characterized for operation from 0°C to +125°C, and it is capable of generating PWM signals up to 350kHz with a duty cycle from 10 to 95%.[1]
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Microprocessor based signal processing techniques for system identification and adaptive control of DC-DC converters

Microprocessor based signal processing techniques for system identification and adaptive control of DC-DC converters

For a high performance controller with high dynamic performance, accurate estimation of the system parameters is essential [5]. Normally, in digitally controlled systems, a discrete time transfer function model of the plant is used for the control design [5, 6]. The actual form of the transfer function, and the numerical values of its coefficients, are dependent upon the individual parameters of the plant to be controlled [54]. It is the fundamental role of the system identification process to evaluate each coefficient of the transfer function. In many applications, it is very important that the coefficients are calculated as accurately as possible, since this will ultimately determine the closed loop controller response. However, in SMPC applications, it is also necessary to acquire the system parameters rapidly. The time constants in PWM switched power converters are often very short, and it is not uncommon for abrupt load changes to be observed. Any system identification scheme must be able to respond appropriately to these characteristics. However, to achieve improved accuracy and/or speed also implies the need for a faster, more powerful microprocessor platform. This is not always viable in SMPC applications, where it is essential to keep system costs low and competitive. Therefore, there is a need for computationally light system identification schemes which enable these advanced techniques to be performed on lower cost hardware.
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Battery Management System For Electric Vehicle Applications

Battery Management System For Electric Vehicle Applications

packs. However, the electric circuit-based model is useful in representing the electrical characteristics of the batteries. The simplest electric circuit-based model consists of an ideal voltage source in series with an internal resistance. Unfortunately, this model does not take the SOC of the battery into account. Therefore, Tremblay used an equation to describe the electrochemical behavior of a battery in terms of the terminal voltage, open- circuit voltage, and internal resistance. The model for the discharge current and SOC was developed by Shepherd, which was applicable to both the discharging and charging processes. However, this model causes an algebraic loop problem in the closed-loop simulation of modular models.
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Performance Analysis of Speed Control of Hybrid Electric Vehicle

Performance Analysis of Speed Control of Hybrid Electric Vehicle

In recent years, the population has increased the demand of conventional internal combustion Engine vehicle (ICEV). Due to heavy demand of ICEV, pollution has increased causing greenhouse effect leading to global warming. For this reason, automobile industries developed HEV, which combines with the Electrical engine and IC engine for delivering the propulsion power. HEV is the very popular now-a-day because of fuel economy and better vehicle Performance. These vehicles have less emission, higher passenger comfort, and increased safety. The modern electric vehicle performance depends very much on automation system applied. There are different types of controllers to get the optimized response for any system. PID is one of the effective conventional controllers that has been used from a long time back. Ziegler-Nichols (ZN) tuning method for PID controller is a popular tuning process [3]. The disadvantage of PID controller is that it is not suitable for higher order nonlinear system. IMC controller is used to decrease the disturbance of the system and to make the system internally stable [6-8]. IMC-PID with fractional filter provides more flexibility in controller design as compared with standard PID controllers [9-10]. Self-tuning Fuzzy PD and self-tuning Fuzzy PID controllers are intelligent controllers that use IF and THEN rule to get optimized result [11-13].
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Dynamic Wireless Electric Vehicle Charging System

Dynamic Wireless Electric Vehicle Charging System

----------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Wireless Power Transfer(WPT) utilizing attractive reverberation is the innovation which could set human free from the irritating wires. Indeed, the WPT embraces a similar essential hypothesis which has just been created for something like 30 years with the term inductive power exchange. Recently WPT innovation is growing rapidly . At kilowatts control level, the exchange separate increments from a few millimeters to a few hundred millimeters with a lattice to stack proficiency above 90%. The makes the WPT very useful to the electric vehicle (EV) charging applications in both stationary and dynamic charging situations. This paper surveyed the advancements in the WPT territory material to EV remote charging. By presenting WPT in EVs, the snags of charging time, range, and cost can be effectively relieved. Battery innovation is never again pertinent in the mass market entrance of EVs. It is trusted that specialists could be supported by the cutting edge accomplishments, and push forward the further improvement of WPT just as the extension of EV.
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Active suspension control of electric vehicle with in-wheel motors

Active suspension control of electric vehicle with in-wheel motors

In a four-wheel independent drive electric vehicle (4WID-EV), the torque of each IWM can be independently controlled. AFS and DYC are two effective ways to enhance the handling and stability of EVs. A fuzzy logic driver-assist stability system for 4WID-EV based on a yaw reference DYC is proposed in [112]. Speed sensor-less fuzzy direct torque control for PMSM driven EV is introduced in [113]. Moreover, the integration control system with active AFS and DYC in 4WID-EV is explored recently. A nonlinear integrated control system which combine AFS and DYC together is proposed for 4WID- EV based on a triple-step nonlinear method [114]. Vehicle lateral motion control for 4WID-EV with the combination of AFS and DYC via in-vehicle networks is studied in [115]. The QP-based torque allocation method, and the message priority scheduling method and generalized PI upper-level controller are used to enhance the lateral performance. A combination of AFS and DYC with good robustness is proposed for 4WID-EVs to deal with in-vehicle network caused time-varying delays issues in [116]. The IWM fault taking place in the 4WID-EV, possibly be resulted from mechanical failures and motor vibration. As a result, the faulty wheel and motor possibly cannot supply enough torque and power. Several fault diagnosis and FLC strategies for 4WID- EV are investigated. An IWM fault diagnosis and FLC method for 4WID-EV is proposed in [117]. A fault-tolerant controller for EV with four-wheel-independent-steering (4WIS) and 4WID is presented in [118] based on a modified SMC method. Active fault tolerant controller for EVs with rear wheel IWMs to improve yaw motion control performance is proposed in [119]. Chukwuma proposes a fault-tolerant IWM design which could achieve a large motor torque, high power density, and maintain a certain level of performance following a failure [120].
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Autonomous Vehicle Density based Traffic Control System

Autonomous Vehicle Density based Traffic Control System

Vehicular traffic congestion is a major issue all over the world due to the increase in urbanization [1]. With the number of people owning vehicles increasing, this problem can only get worse with time. Aside this, traffic congestion contributes to environmental pollution and unpredictable travel times [2]. To curtail this problem, traffic lights were introduced. Much as the standard traffic lights have helped alleviate congestion on roads, they have at times been the culprits of congestion. Standard traffic lights ensure vehicles at an intersection proceed from each direction in a fixed amount of time [3]. This system does not take into consideration constantly changing traffic flow and the likelihood of an unbalanced density of vehicles waiting to proceed from each direction at the intersection. This causes the situation where there are no vehicles at a section of the intersection, yet there is a signal for vehicles from that section to proceed whilst other vehicles at the other sections have been signalled to wait. This causes an unnecessary waste of time at intersections and also contributes to traffic congestion, especially during rush hours [1].
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A New Zonal Based Vehicle Speed Control System

A New Zonal Based Vehicle Speed Control System

This paper begins by identifying three stages in the likely evolution of these advanced vehicle control systems (AVCS), showing how AVCS is related to the other IVHS functions. The technological elements of AVCS, corresponding to needed research and development work, are then described. The international state of the art in these technologies is reviewed, and the paper concludes with a discussion of an evolutionary progression that could be followed to lead from present-day driving to the long-term concept of an automated freeway network.

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Vision based autonomous vehicle driving control system

Vision based autonomous vehicle driving control system

LITERATURE REVIEW Sensors Cameras Infrared Magnetic Radar Lane Detection Using Image Processing and Analysis Process Related Research Review Edge Detection Hough Transform Vehicle Modell[r]

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Development of telemetry system for electric powered vehicle

Development of telemetry system for electric powered vehicle

Telemetry is an automated communications process by which measurements and other data are collected at remote or inaccessible points and transmitted to receiver for monitoring ., 2009). Most activities in agriculture is need to sly. Quality of the yields and health of the crops is depends on how can you reach to available data. It has become a major challange to control the growth of energy consumption with the acceleration of agricultural mechanization in Turkey, which causing the increasing dependency on energy sources such as fossil fuels. Fossil fuels are environmentaly polluted and expensive (Hammad 1996). Clean and renewable energy solutions are started to use in In agriculture during last years, farmers have passed from the use of big tractors to the use of small and efficient vehicles. Electrical vehicles are used in agriculture for different purposes like farms, nurseries, greenhouses and vineyards. They are giving advantage to s by their compact dimensions and efficient power usage
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Skid control of small electric vehicle with hydraulic-mechanical hybrid brake system

Skid control of small electric vehicle with hydraulic-mechanical hybrid brake system

Fig.lO shows the model of a hydraulic-mechanical brake system represented as two wheel drive vehicle and both left and right side of the brake system have the same mechanism. The front[r]

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