Fuzzy Logic Controller for Parallel Plug-In Hybrid Vehicle Sk
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University of Wisconsin Milwaukee UWM Digital Commons Theses and Dissertations December 2012 Fuzzy Logic Controller for Parallel Plug-in Hybrid Vehicle Sk. Khairul Hasan University of Wisconsin-Milwaukee Follow this and additional works at: https://dc.uwm.edu/etd Part of the Electrical and Computer Engineering Commons, and the Mechanical Engineering Commons Recommended Citation Hasan, Sk. Khairul, "Fuzzy Logic Controller for Parallel Plug-in Hybrid Vehicle" (2012). Theses and Dissertations. 436. https://dc.uwm.edu/etd/436 This Thesis is brought to you for free and open access by UWM Digital Commons. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of UWM Digital Commons. For more information, please contact [email protected]. FUZZY LOGIC CONTROLLER FOR PARALLEL PLUG-IN HYBRID VEHICLE by Sk. Khairul Hasan A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering at The University of Wisconsin-Milwaukee December 2012 ABSTRACT FUZZY LOGIC CONTROLLER FOR PARALLEL PLUG-IN HYBRID VEHICLE By Sk. Khairul Hasan The University of Wisconsin-Milwaukee, 2012 Under the supervision of Dr. Anoop K. Dhingra Hybrid electric vehicles combine two methods for propelling a vehicle. In a parallel hybrid vehicle, the two propulsion methods work in parallel to meet the total power demand. Among different combination of power sources, internal combustion engine and electric motor drive system are the most popular because of their availability and controllability. Plug-in hybrid vehicle is the latest version in hybrid vehicle family. In plug-in hybrid vehicle, battery is directly recharged from the electrical power grid and it can be used for a long distance with higher efficiency. Most of the hybrid vehicles on the road are parallel in nature and battery is recharged directly by the engine. If it is possible to convert existing hybrid vehicle into plug-in hybrid vehicle, it will lead to significant improvements in fuel economy and emissions. ii In this thesis, two fuzzy logic controllers have been developed for the energy management system of the hybrid vehicle. For the first controller, it is assumed that the vehicle will work like a plug-in hybrid vehicle. For the second controller it is assumed that the battery will always recharged by the engine. It is found that with the help of developed fuzzy logic controller, the plug-in hybrid vehicle can run up to 200 miles with high efficiency. Both controllers are developed and their performance is tested on the highly reliable vehicle modeling and simulation software AUTONOMIE. The main objective of developing the controllers is increasing the fuel economy of the vehicle. The results from the both developed controllers are compared with the default controller in AUTONOMIE in order to show performance improvements. iii © Copyright by Sk. Hasan, 2012 All Rights Reserved iv Dedicated with all my love to my parents and my respected teacher Dr. Mozasser Rahman v TABLE OF CONTENTS 1. Introduction………………………………………………………………….…………………………...… 1 1.1. Hybrid Vehicles………………………………………………………………………………………………. 1 1.1.1. Parallel Hybrid vehicle…………………………………………………………………………… 4 1.1.2. Series Hybrid vehicle……………………………………………………………………...……… 6 1.1.3. Power split hybrid electric vehicle……………………………………..……………………8 1.2. Literature Review…………………………………………………………………………….………………9 1.3. Thesis Organization…………………………………………………………………..……………………17 2. Modeling……………………………………………………………………………………………………… 19 2.1. Engine ………………………………………………………………………………….…..………….……….21 2.2. Mechanical accessories …………………………………………………………………………………22 2.3. Battery model………………………………………………………………………………………23 2.4. Automatic Clutch …………………………………………………….………………………….…………23 2.5. Gearbox ………………………………………………………………………………………..………………23 2.6. Final drive …………………………………………………………………………………………...….……24 2.7. Wheels and axle Motor ………………………………………………………………….….…….……24 vi 2.8. Chassis ……………………………………………………………………….……………….……….……….26 2.9. Vehicle Model…………………………………………………………………….………………….……..26 2.10. Model of the Electric motor…………………………………………………………….…….…28 2.11. Driver Block ………………………………………………………………………………………………29 2.12. Environment Block …………………………………………………………..………………………30 2.13. Driving Cycle…………………………………………………………………………….………………31 3. Fuzzy logic based controller …………………………………………………….………….….……37 3.1. Fuzzy sets…………………………………………………………………………………..….…………..…39 3.2. Fuzzification process………………………………………………………………………..…...….…43 3.3. Rule base fuzzy inference system…………………………………………………………….……45 3.4. Determining firing strength……………………………………………………………….……..….45 3.5. Defuzzification process…………………………………………………………………………..……47 4. Simulation…………………………………………………………………………………………………56 4.1. Simulation setup……………………………………………………………………………………………56 4.2 Simulation and result analysis of developed fuzzy logic controller based vehicle in UDDS cycle……………………59 vii 5. Conclusions and recommendations………………………………………………..………………….79 5.1. Conclusion……………………………………………………….……………………………………………………79 5.2. Recommendation…………………………………………………………………………………………………81 References……………………………………………………………………………….………………………………82 viii LIST OF FIGURES Figure 1.1 Total fuel consumption by sector in year 2010………………………………..…..……….2 Figure 1.2 Total fuel consumption by sector from year 1949 to 2010………………….…..……2 Figure 1.3 Comparison between different type of vehicle configurations ………………..……5 Figure 1.4 Power flow architecture of Parallel hybrid vehicle………………………….……..……6 Figure 1.5 Power flow architecture of Series hybrid vehicle………………………….………………7 Figure 1.6 Power flow architecture of Power split hybrid vehicle……………………………..…..9 Figure 2.1 Parallel ISG mid-size parallel hybrid vehicle’s energy flow diagram……..……20 Figure 2.2 ECOTECH GM family ІІ engine…………………………………………………………………...21 Figure: 2.3 Engine efficiency map……………………………………………………………………..………..22 Figure 2.4 Internal architecture of the battery…………………………………………………...……….24 Figure 2.5 Wheels……………………………………………………………………………………………………..…25 Figure 2.6 free body diagram of the vehicle………………………………………………….…………….27 Figure 2.7 Permanent magnet DC motor………………………………………………………….…………29 Figure 2.8 Motor efficiency maps…………………………………………………………………….…………30 Figure 2.9 UDDS driving cycle. ………………………………………………………………………….…………32 ix Figure 2.10 HWFET Cycle…………………………………………………………………………………………….33 Figure 2.11 NEDC low speed cycle…………………………………………………………………….…………34 Figure 3.1 Block diagram of Fuzzy Logic Control System…………………………….……….………38 Figure 3.2 membership function of Battery SOC …………………………………………………………40 Figure 3.3 Membership function of wheel equivalent torque demand…………………………41 Figure 3.4 Membership functions of vehicle speed……………………………………………..….……41 Figure 3.5 Membership functions of engine speed. …………………………………………..…..……42 Figure 3.5 Membership functions of engine torque demand…………….............................42 Figure: 3.6 Membership functions of motor torque demand………………………………………..43 Figure 3.7 Fuzzification of battery SOC………………………………………………………………..….……43 Figure 3.8 Fuzzification of equivalent wheel torque demand………………………………….……44 Figure 3.9 Fuzzification of equivalent vehicle speed demand………………………….…...………44 Figure 3.10 Center of area defuzzification method……………………………………….…….….……47 Figure 3.11 Smallest of maxima defuzzification method…………………………………….…………48 Figure 3.12 SOC, speed versus engine torque (Controller 1)…………………………..……..….…48 Figure 3.13 SOC, driver torque demand versus engine torque (Controller 1)….……...……49 Figure 3.14 speed, driver torque demand versus engine torque (Controller 1)…….….....49 x Figure 3.15 SOC, speed versus motor torque (Controller 1)…………………………………….…..50 Figure 3.16 speed driver torque demand versus motor torque (Controller 1)………….….50 Figure 3.17 SOC, driver torque demand versus motor torque (Controller 1)……………..…51 Figure 3.18 SOC, speed versus motor torque (Controller 1)…………………………………….…..51 Figure 3.19 Speed, driver torque demand versus engine torque (Controller 2)…….……..52 Figure 3.20 Speed, SOC versus motor torque (Controller 2)……………………………………..….52 Figure 3.21 SOC, driver torque demand versus engine torque (Controller 2)………...….…53 Figure 3.22 SOC, driver torque demand versus motor torque (Controller 2)……….……....53 Figure 3.23 Speed, driver torque demand versus motor torque (Controller 2)………..……54 Figure 4.1 UDDS driving cycle………………………………………………………………………….……….…..60 Figure 4.2 Output vehicle speed using controller 1…………………………………………….…….….60 Figure 4.3 Output vehicle speed using controller 2…………………………………….….…….….…..60 Figure 4.4 Battery SOC using controller 1…………………………………………………………….….……62 Figure 4.5 Battery SOC using controller 2………………………………………………………….…….……62 Figure 4.6 Engine output torque using controller 1……………………………………….…..…………63 Figure 4.7 Engine output torque using controller 2…………………………………………....…..……63 Figure 4.8 Motor output torque using controller 1………………………………………..………..……63 xi Figure 4.9 Motor output torque using controller 2………………………………………………….……64 Figure 4.10 Engine ON demand simulation using controller 1………………………………………64 Figure 4.11 Engine ON demand simulation using controller 2……………………………..….……65 Figure 4.12 Total fuel consumption by engine using controller 1………………………..….……66 Figure 4.13 Total fuel consumption by engine using controller 2………………………..….……66 Figure 4.14 Engine fuel consumption rate using controller 1…………………………….………….67 Figure 4.15 Engine fuel consumption rate using controller 2…………………………….…………67 Figure 4.16 Battery output current simulation using controller 1………………….…………….68 Figure 4.17 Battery output