PTEE3031 Intelligent Control of Electric Vehicles Syllabus:
PTEE3031 Intelligent Control of Electric Vehicles Syllabus – Anna University Part time Regulation 2023
COURSE OBJECTIVES:
To design and drive the mathematical model of a BLDC motor and its characteristics
To learn the different control schemes for BLDC motor
To study the basics of fuzzy logic
To study the FPGA & VHDL basics
To implement fuzzy logic control of BLDC motor in real time
UNIT I MATHEMATICAL MODEL AND CHARACTERISTICS ANALYSIS OF THE
BLDC MOTOR
Structure and Drive Modes – Basic Structure, General Design Method, Drive Modes. Mathematical Model, Differential Equations, Transfer Functions, State-Space Equations. Characteristics Analysis, Starting Characteristics, Steady-State Operation, Dynamic Characteristics, Load Matching Commutation Transients
UNIT II SPEED CONTROL FOR ELECTRIC DRIVES
Introduction -PID Control Principle, Anti windup Controller, Intelligent Controller. Vector Control. Control applied to BLDC motor.
UNIT III FUZZY LOGIC
Membership functions: features, fuzzification, methods of membership value assignments Defuzzification: lambda cuts – methods – fuzzy arithmetic and fuzzy measures: fuzzy arithmetic – extension principle – fuzzy measures – measures of fuzziness -fuzzy integrals – fuzzy rule base and approximate reasoning : truth values and tables, fuzzy propositions, formation of rules decomposition of rules, aggregation of fuzzy rules, fuzzy reasoning-fuzzy inference systems, overview of fuzzy expert system-fuzzy decision making.
UNIT IV FPGA AND VHDL BASICS
Introduction – FPGA Architecture-Advantages-Review of FPGA family processors- Spartan 3, Spartan 6 and Spartan 7. VHDL Basics- Fundamentals-Instruction set-data type-conditional statements- programs like arithmetic, sorting, PWM generation, Speed detection.
UNIT V REAL TIME IMPLEMENTATION
Inverter design, identifying rotor position via hall effect sensors, open loop and fuzzy logic control of 48 V BLDC motor using FPGA.
30 PERIODS
LAB COMPONENT: 30 PERIODS
1. Design and simulate speed controller for induction motors in EV for both dynamic and steady state performance
2. Simulate a fuzzy logic controller based energy storage system for EV.
3. Fuzzy logic control of BLDC motor using FPGA in real time
TOTAL: 30+30 = 60 PERIODS
COURSE OUTCOMES:
Upon the successful completion of the course, students will be able to:
CO1: To design the mathematical model of a BLDC motor and to discuss about its characteristics
CO2: To demonstrate the PID control, ant windup controller, Intelligent Controller and Vector Control. Control applied to BLDC motor.
CO3: To illustrate the basics of fuzzy logic system
CO4: To describe the basics of VHDL & FPGA applied to control of EVs.
CO5: To design and implement of fuzzy logic control scheme for BLDC motor using FPGA in real time.
REFERENCES:
1. Electric Powertrain Energy Systems, Power Electronics and Drives for Hybrid, Electric and Fuel Cell Vehicles, John G. Hayes, G. Abas Goodarzi, Wiley 1st Edition 2018.
2. VHDL Primer, A (3rd Edition), Jayaram Bhasker, Prentice Hall, 1st Edition 2015.
3. Iqbal Hussain, “Electric and Hybrid Vehicles: Design Fundamentals, Third Edition” CRC Press, Taylor & Francis Group, 2021, 1st Edition.
4. Chang-liang, Permanent Magnet Brushless DC Motor Drives and Controls, Xia Wiley 2012, 1st Edition.
5. M.N. Cirstea, A. Dinu, J.G. Khor,M. McCormick, Neural and Fuzzy Logic Control of Drives and Power Systems, Newnes publications, 1st Edition, 2002.
6. Wei Liu, Hybrid Electric Vehicle System Modeling and Control, Wiley 2017, 2nd Edition
7. Electric and Plug-in Hybrid Vehicle Networks Optimization and Control, Emanuele Crisostomi Robert Shorten, Sonja Stüdli • Fabian Wirth, CRC Press, 1st Edition. 2018.