Idea for New Research

Online Electric Vehicle Control Using Fuzzy Logic Controller Hitech Solutions, Veppamoodu junction, Nagercoil. India. Email id- [email protected] Mobile No-+91 9994879483, www.hitechsolutions.info Abstract The On-Line Electric Vehicle (OLEV) is a novel electricity powered transportation system which eliminates the disadvantages of ordinary vehicle. Market demand and socio economic requirements insist the need for online electric vehicle. Online electric vehicle control plays an important role. For that purpose fuzzy controller is introduced in this paper. Fuzzy control has become an attractive control in recent years. Conventional control design techniques have been difficult to apply in some situations. Fuzzy control has been widely used in that situation. Number of fuzzy rules is very important for real time fuzzy control applications. This increased popularity of the fuzzy control can be attributed to the fact that fuzzy logic systems provide a powerful vehicle that allows engineers to incorporate human reasoning in the control algorithm. Overshoot protection and output voltage regulation of converter can be done effectively using fuzzy control. Index terms - Online Electric vehicle (OLEV), Fuzzy logic controller (FLC), Electric vehicles (EVs)

1. Introduction Nowadays, increase in the interest of energy conservation across industries implicit to obtain reliable technical solutions according to minimize the energy consumption. In the past few years, the concept of energy efficiency has obtained a lot of attention in the field of power system. Active research is being executed to find solutions for increasing energy efficiency and motivating the implementation of distributed sources of generation near the load centers for the purpose of power loss. However, the main disadvantages of Electric Vehicles (EVs) are that owing to the limited energy density of the batteries, requirement in larger battery sizes are needed thereby resulting in higher costs. OLEV is an electricity powered transportation system which remotely picks up electricity from power transmitters buried underground. The power transmitters

inductive cables buried under the roadway generate a magnetic field to supply the vehicle with needed energy. The power pick-up unit installed underneath the vehicle remotely collects electricity and distributes the power either to operate the motor in the vehicle or to charge the battery. Whether running or being stopped, the OLEV constantly receives electric power through the underground cables. As a result, the OLEV mitigates the burden of equipping electric the vehicle with heavy and bulky batteries. The OLEV system undergoing research utilizes a power inverter developed particularly for this system, where the 440V, ac, three phases, 60Hz input is converted to dc which then is converted to generate a 20 kHz ultrahigh frequency voltage by using insulated-gate bipolar transistor (IGBT) devices. Fuzzy control systems are developed based on fuzzy mathematics. It is a branch of applied mathematics and it has found broad applications in various fields including signal and image processing, systems and control engineering, statistics and numerical analysis, pattern recognition, and biomedical engineering. Furthermore, fuzzy mathematics was applied to control systems, in both theory and engineering. Advances in modern computer technology have been steadily backing up the fuzzy mathematics for coping with engineering systems of a broad spectrum, including many control systems that are too complex to tackle by conventional control theories and techniques. The essence of systems control is to achieve automation. A combination of fuzzy control technology and advanced computer facility accessible in the industry gives a promising approach that can mimic human thinking and linguistic control ability, so as to provide the control systems with certain degree of artificial intelligence. It has now been perceived that fuzzy control systems theory and methods offer a, realistic, simple and successful alternative for the control of imperfectly modeled, complex and highly uncertain engineering systems. Fuzzy control technology appears to have a bright future in many real world applications; its great potential in industrial automation should be further explored.

Idea for New Research

In this paper, propose an online electric online electric vehicle control using fuzzy logic controller. OLEV plays an important role. For that purpose fuzzy controller is introduced in this paper. Fuzzy control has become an attractive control in recent years. Existing control design techniques have been difficult to apply in some situations. Fuzzy control has been extensively used in that situation.

the error in near future and thus to decrease a reaction time of the controller.

R

+

e

u P

I

2. Existing Method The dc distribution system is being proposed to enable electricity exchange between the substations similar to other dc based transportation systems. Then the system is constructed based on the given line information, the scheduling being executed which reflects the consumption power of the vehicle and the charging power of inverter for the efficient operation of the whole system. Here, PI controller used to control the online electric vehicle. In fig.1 illustrates the existing method for OLEV with PI Controller.

AC supply

Inverter

Buck converter

Output

PI Controller

Fig.1 Existing method for OLEV with PI controller PI controller In fig.2 illustrates block of PI controller. PI controller will remove forced oscillations and steady state error resulting in operation of on-off controller and P controller respectively. Whenever, introducing integral mode has a negative effect on speed of the response and overall stability of the system. PI controller will not enlarge the speed of response. It can be anticipated since PI controller does not have means to predict what will happen with the error in near future. This problem can be solved by introducing derivative mode which has ability to predict what will happen with

Converter

Y

Controller Block

Fig.2 Block diagram of PI controller The Proportional and integral term is given by, u(t) = e(t) + dt and are the tuning knobs, are adjusted to obtain the desired output.

3. Proposed method The block diagram for proposed OLEV with fuzzy logic controller is illustrated in fig.3. In OLEV, AC is converted to DC by using inverter. The inverter output is given to the buck converter. The buck converter is controlled by using Fuzzy logic controller. Fuzzy control is replaces the complex mathematical model and introduces new set of rules. The inputs and outputs of the system have remained unchanged. The behavior of the system is controlled by changing an input or input to the system according to that rule or set of rules. Fuzzy control is provides greater efficiency when compared to PI control which is based on mathematical operation. AC supply

Inverter

Buck converter

Output

Fuzzy logic controller

Fig.3 Block diagram for proposed OLEV with fuzzy logic controller

Idea for New Research Fuzzy logic controller Generally, PD, PI and PID controller are most popular controllers and they are widely used in most power electronics close loop appliances, But in the current year there are various researchers reported successfully acquired the Fuzzy Logic Controller (FLC) to become one of intelligent controllers. FLC is comprises a way of converting linguistic control strategy into an automatic by generating a rule base which controls the behavior of the system. Fuzzy control is control method and it based on fuzzy logic. It provides a remarkably simple way to draw definite conclusions from vague ambiguous or imprecise information.

Rule base e Fuzzifier

Decision Making

Defuzzifier

4) The defuzzification interface converts the obtained fuzzy value from the inference engine to crisp value. The two inputs to the fuzzy controller are, 1) The voltage error (e) (reference voltage subtracted from actual voltage) 2) The change in voltage error (ce) (previous error subtracted from current error over one sample period).

Fuzzy Logic Membership Function The buck dc-dc converter is a nonlinear function of the duty cycle because of the small signal model and its control method was applied to the control of buck converters. In Fuzzy controllers mathematical model is not require. Alternatively, they are designed based on general knowledge of the converter. The Fuzzy controllers are designed to acquire the varying operating points. FLC is designed to control the output of buck dc-dc converter.

4. Experimental Result This model is developed in Simulink / Matlab.

ce Data base

Buck converter Vo

dK

Vref

Fig.5 Simulink diagram for proposed method

Fig.4 Block Diagram of FLC for Buck converter In fig.4 illustrates the block diagram Fuzzy Logic controller (FLC) for buck converter. Fuzzy logic control has 4 major components. There are, 1) Fuzzification interface that converts crisp value to fuzzy value. The output from the process will always be crisp. 2) The rule base, it is a collection of rules referring to a particular system. 3) The inference mechanism compares the output from the fuzzification module and that from fuzzy rule base generating an inference output based on the type of condition selected and

Fig.6 Fuzzy buck converter output voltage

Idea for New Research

Fig.7 battery 5. Conclusion Online electric vehicle control using fuzzy logic is implemented. Design of fuzzy logic controller on buck converter by using MATLAB has been implemented successfully. Algorithm based on fuzzy logic controller is more convenient than other circuit. Fuzzy controller provides nonlinear control to converter, good transient response, lower rise time, peak time, settling time with higher output voltage can be obtained by using fuzzy controller.

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