A Low-Cost High Performance Electric Vehicle Design Based on Variable Structure Fuzzy PID Control
Abstract
This paper introduces the design steps and implementation of Electric Vehicle (EV) based on variable structure fuzzy PID control. The role of fuzzy logic is making change in the membership function to tune the fuzzy action according to the error and change of error. The control implementation was executed using a low-cost Arduino mega 2560 and had been programed by MATLAB SIMULINK. Also, a nonlinear model for the EV was built and validated by the actual performance of the EV experimental setup. The overall EV closed loop implemented on the MATLAB SIMULINK to select the proper control parameters. The proposed variable structure fuzzy PID control had been compared to the traditional PID control to ensure robustness and reliability. The results show that the proposed control technique can deal with the EV disturbances and continuous change in the operating points.
Keywords
Full Text:
PDFReferences
R. He, Y. Yan, and D. Hu, “Optimised adaptive control methodology for mode transition of hybrid electric vehicle based on the dynamic characteristics analysis,” Veh. Syst. Dyn., vol. 59, no. 8, pp. 1282–1303, 2021, doi: 10.1080/00423114.2020.1752923.
M. H. B. Chaleshtari, E. Norouzi, and H. Ahmadi, “Optimizing control motion of a human arm with PSO-PID controller,” J. Comput. Appl. Res. Mech. Eng., vol. 7, no. 1, pp. 23–34, 2017, doi: 10.22061/JCARME.2017.645.
Y. Gong, Y. Liu, and Z. Tang, “Path tracking of unmanned vehicle based on parameters self-tuning fuzzy control,” 2013 IEEE Int. Conf. Cyber Technol. Autom. Control Intell. Syst. IEEE-CYBER 2013, pp. 52–57, 2013, doi: 10.1109/CYBER.2013.6705419.
C. Abeykoon, “Control Engineering Practice Single screw extrusion control : A comprehensive review and directions for improvements,” Control Eng. Pract., vol. 51, pp. 69–80, 2016, doi: 10.1016/j.conengprac.2016.03.008.
T. Arora and Y. Gigras, “A Survey Of Comparison Between Various Meta -,” Int. J. Comput. Eng. Sci., vol. 3, no. 2, pp. 62–66, 2013.
P. P. Du, H. Su, and G. Y. Tang, “Friction compensation control for electric power steering systems,” Proc. - 2018 IEEE Int. Conf. Ind. Electron. Sustain. Energy Syst. IESES 2018, pp. 212–217, 2018, doi: 10.1109/IESES.2018.8349876.
M. A. Shamseldin, M. Salah, A. G. Mohamed, and M. A. A. Ghany, “A COVID-19 Based on Fractional Order Integral-Tilt Derivative Controller for Nonlinear Servomechanism Model,” Int. J. Electr. Eng. Comput. Sci., vol. 5, pp. 175–182, 2023, doi: 10.37394/232027.2023.5.19.
Z.-J. Guo and X.-Y. Kang, “Modeling and Analysis of Vehicle with Wind-solar Photovoltaic Hybrid Generating System,” in 4th International Conference on Sustainable Energy and Environmental Engineering, pp. 566–570, 2016, doi: 10.2991/icseee-15.2016.95.
Y. Qi, H. Dai, P. Wu, F. Gan, and Y. Ye, “RSFT-RBF-PSO: a railway wheel profile optimisation procedure and its application to a metro vehicle,” Veh. Syst. Dyn., vol. 60, no. 10, pp. 3398–3418, 2022, doi: 10.1080/00423114.2021.1955135.
P. Rodriguez-ayerbe, D. Dumur, S. Lavernhe, P. Rodriguez-ayerbe, D. Dumur, and S. Lavernhe, “Axis control using model predictive control : identification and friction effect reduction Axis control using model predictive control : identification and friction effect reduction,” in 3rd International Conference on Virtual Machining Process Technology, 2014.
R. Papdeja and P. Sankala, “Modelling and Simulation of Three Phase Brushless DC Motor With Using Model Reference Adaptive Controller,” Int. J. Invent. Comput. Sci. Eng., vol. 1, no. 3, 2014.
M. R. Awal, M. Jusoh, M. N. Sakib, F. S. Hossain, M. R. Che Beson, and S. A. Aljunid, “Design and implementation of Vehicle Mounted Wind Turbine,” ARPN J. Eng. Appl. Sci., vol. 10, no. 19, pp. 8699–8706, 2015.
A. . Ouda and A. Mohamed, “Autonomous Fuzzy Heading Control for a Multi-Wheeled Combat Vehicle,” Int. J. Robot. Control Syst., vol. 1, no. 1, pp. 90–101, Apr. 2021, doi: 10.31763/ijrcs.v1i1.286.
S. A. Deraz, “Genetic Tuned PID Controller Based Speed Control of DC Motor Drive,” IJETT, vol. 17, no. 2, pp. 88–93, 2014.
M. A. Shamseldin, “Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle Mohamed,” J. Robot. Control, vol. 3, no. 5, p. 546, 2022.
M. A. Shamseldin, “Optimal Covid-19 Based PD/PID Cascaded Tracking Control for Robot Arm driven by BLDC Motor,” Wseas Trans. Syst., vol. 20, pp. 217–227, 2021, doi: 10.37394/23202.2021.20.24.
M. A. Shamseldin et al., “A New Design Identification and Control Based on GA Optimization for an Autonomous Wheelchair,” Robotics, vol. 11, no. 5, p. 101, 2022.
M. A. Shamseldin, “Optimal Coronavirus Optimization Algorithm Based PID Controller for High Performance Brushless DC Motor,” Algorithms Artic., vol. 14, p. 17, 2021.
Y. Zahraoui, M. Akherraz, and A. Ma’arif, “A Comparative Study of Nonlinear Control Schemes for Induction Motor Operation Improvement,” Int. J. Robot. Control Syst., vol. 2, no. 1, pp. 1–17, 2021, doi: 10.31763/ijrcs.v2i1.521.
E. S. Rahayu, A. Ma’arif, and A. Çakan, “Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor,” Int. J. Robot. Control Syst., vol. 2, no. 2, pp. 435–447, 2022.
F. Piltan, A. Taghizadegan, and N. B. Sulaiman, “Modeling and Control of Four Degrees of Freedom Surgical Robot Manipulator Using MATLAB/SIMULINK,” International Journal of Hybrid Information Technology, vol. 8, no. 11, pp. 47–78, 2015.
X. Wei-hong, C. Li-jia, and Z. Chun-lai, “Review of Aerial Manipulator and its Control,” Int. J. Robot. Control Syst., vol. 1, no. 3, pp. 308–325, 2021, doi: 10.31763/ijrcs.v1i3.363.
M. Drive, “Modeling and Analysis of PI Controller Based Speed Control of Brushless DC Motor Drive,” IJESRT, vol. 2, no. 9, pp. 7–12, 2013.
A. Info, “A Survey of Control Methods for Quadrotor UAV,” Int. J. Robot. Control Syst., vol. 2, no. 4, pp. 652–664, 2022.
C. S. R. Reddy and M. S. Kalavathi, “Performance Analysis of BLDC Motor Drive using New Simulation Model with Fuzzy and ANFIS Speed Controllers,” Glob. J. Res. Eng. F Electr. Electron. Eng., vol. 14, no. 4, 2014.
M. A. Abdel Ghany and M. A. Shamseldin, “Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model applied on Egyptian load frequency control,” Int. J. Electr. Comput. Eng., vol. 10, no. 5, pp. 5274–5287, 2020, doi: 10.11591/IJECE.V10I5.PP5274-5287.
A. A. Kesarkar and N. Selvaganesan, “Systems Science & Control Engineering Tuning of optimal fractional-order PID controller using an artificial bee colony algorithm,” Syst. Sci. Control Eng., vol. 2583, no. November, 2015, doi: 10.1080/21642583.2014.987480.
L. M. El-Τehewy, M. Α. Shamseldin, M. Sallam, and Α. M. Abdel Ghany, “A Modified Model Reference Adaptive Control for High-Performance Pantograph Robot Mechanism,” Wseas Trans. Appl. Theor. Mech., vol. 16, pp. 193–203, 2021, doi: 10.37394/232011.2021.16.22.
M. A. Shamseldin, M. Sallam, A. M. Bassiuny, and A. A. Ghany, "Real-time implementation of an enhanced nonlinear PID controller based on harmony search for one-stage servomechanism system," Journal of Mechanical Engineering and Sciences, vol. 12, no. 4, pp. 4161-4179, 2018.
A. L. Elshafei, K. A. El-Metwally, and A. A. Shaltout, “A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems,” Control Eng. Pract., vol. 13, no. 4, pp. 413–423, 2005, doi: 10.1016/j.conengprac.2004.03.017.
V. Pshikhopov and M. Medvedev, "Position-path control of a vehicle," Path Planning for Vehicles Operating in Uncertain 2D Environments, pp. 1-23, 2017, doi: 10.1016/B978-0-12-812305-8.00001-6.
R. Sharma, S. Bhasin, P. Gaur, and D. Joshi, “A switching-based collaborative fractional order fuzzy logic controllers for robotic manipulators,” Appl. Math. Model., vol. 73, pp. 228–246, 2019, doi: 10.1016/j.apm.2019.03.041.
M. A. George, D. V. Kamat, and C. P. Kurian, “Electric vehicle speed tracking control using an ANFIS-based fractional order PID controller,” Journal of King Saud University-Engineering Sciences, vol. 36, no. 4, pp. 256-264, 2022, doi: 10.1016/j.jksues.2022.01.001.
A. X. R. Irudayaraj et al., “A Matignon’s theorem based stability analysis of hybrid power system for automatic load frequency control using atom search optimized FOPID controller,” IEEE Access, vol. 8, pp. 168751–168772, 2020, doi: 10.1109/ACCESS.2020.3021212.
M. U. Jan, A. Xin, M. A. Abdelbaky, H. U. Rehman, and S. Iqbal, “Adaptive and Fuzzy PI Controllers Design for Frequency Regulation of Isolated Microgrid Integrated with Electric Vehicles,” IEEE Access, vol. 8, no. 1, pp. 87621–87632, 2020, doi: 10.1109/ACCESS.2020.2993178.
I. S. Akkizidis, G. N. Roberts, P. Ridao, and J. Batlle, “Designing a Fuzzy-like PD controller for an underwater robot,” Control Eng. Pract., vol. 11, no. 4, pp. 471–480, 2003, doi: 10.1016/S0967-0661(02)00055-2.
A. G.Preethi and A. B.Santhi, “Study on Techniques of Earthquake Prediction,” Int. J. Comput. Appl., vol. 29, no. 4, pp. 55–58, 2011, doi: 10.5120/3549-4867.
A. Ghanbari, S. M. R. Kazemi, F. Mehmanpazir, and M. M. Nakhostin, “A cooperative ant colony optimization-genetic algorithm approach for construction of energy demand forecasting knowledge-based expert systems,” Knowledge-Based Syst., vol. 39, no. 2013, pp. 194–206, 2013, doi: 10.1016/j.knosys.2012.10.017.
X. Xu, M. Wang, P. Xiao, J. Ding, and X. Zhang, “In-Wheel Motor Control System for Four-Wheel Drive Electric Vehicle Based on CR-GWO-PID Control,” Sensors, vol. 23, no. 19, 2023, doi: 10.3390/s23198311.
R. Zhai, P. Xiao, R. Zhang, and J. Ju, “In-wheel motor control system used by four-wheel drive electric vehicle based on whale optimization algorithm-proportional–integral–derivative control,” Adv. Mech. Eng., vol. 14, no. 6, pp. 1–16, 2022, doi: 10.1177/16878132221104574.
T. H. S. Li and Y. C. Huang, “MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators,” Inf. Sci. (Ny)., vol. 180, no. 23, pp. 4641–4660, 2010, doi: 10.1016/j.ins.2010.08.009.
A. Bahadir and Ö. Aydoğdu, “Modeling of a brushless dc motor driven electric vehicle and its pid-fuzzy control with dSPACE,” Sigma J. Eng. Nat. Sci., vol. 41, no. 1, pp. 156–177, 2023, doi: 10.14744/sigma.2023.00015.
R. C. Dorf and R. H. Bishop. Modern control systems solution manual. Addison-Wesley, 1998.
E. M. Ahmed, E. A. Mohamed, A. Elmelegi, M. Aly, and O. Elbaksawi, “Optimum Modified Fractional Order Controller for Future Electric Vehicles and Renewable Energy-Based Interconnected Power Systems,” IEEE Access, vol. 9, pp. 29993–30010, 2021, doi: 10.1109/ACCESS.2021.3058521.
J. Peng and R. Dubay, “Identification and adaptive neural network control of a DC motor system with dead-zone characteristics,” ISA Trans., vol. 50, no. 4, pp. 588–598, 2011, doi: 10.1016/j.isatra.2011.06.005.
K. Premkumar and B. V. Manikandan, “Fuzzy PID supervised online ANFIS based speed controller for brushless dc motor,” Neurocomputing, vol. 157, pp. 76–90, 2015, doi: 10.1016/j.neucom.2015.01.032.
I. Silva and J. E. Naranjo, “A systematic methodology to evaluate prediction models for driving style classification,” Sensors, vol. 20, no. 6, pp. 1–21, 2020, doi: 10.3390/s20061692.
A. C. Sánchez, J. F. Figueroa-Rodríguez, A. G. Fuentes-Covarrubias, R. Fuentes-Covarrubias, and S. K. Gadi, “Recycling and updating an educational robot manipulator with open-hardware-architecture,” Sensors, vol. 20, no. 6, pp. 1–22, 2020, doi: 10.3390/s20061694.
J. R. García-Martínez, E. E. Cruz-Miguel, R. V. Carrillo-Serrano, F. Mendoza-Mondragón, M. Toledano-Ayala, and J. Rodríguez-Reséndiz, “A PID-type fuzzy logic controller-based approach for motion control applications,” Sensors, vol. 20, no. 18, pp. 1–19, 2020, doi: 10.3390/s20185323.
L. Xu, Z. Wang, Y. Liu, and L. Xing, “Energy allocation strategy based on fuzzy control considering optimal decision boundaries of standalone hybrid energy systems,” J. Clean. Prod., vol. 279, p. 123810, 2021, doi: 10.1016/j.jclepro.2020.123810.
P. Swethamarai and P. Lakshmi, “Adaptive-Fuzzy Fractional Order PID Controller-Based Active Suspension for Vibration Control,” IETE J. Res., vol. 68, no. 5, pp. 3487–3502, 2022, doi: 10.1080/03772063.2020.1768906.
M. Veysi, J. Aghaei, M. Shasadeghi, R. Razzaghi, B. Bahrani, and D. J. Ryan, “Energy-Efficient Speed Control of Electric Vehicles: Linear Matrix Inequality Approach,” IEEE Trans. Veh. Technol., vol. 69, no. 10, pp. 10469–10483, 2020, doi: 10.1109/TVT.2020.3008500.
X. Wu, Y. Xu, J. Liu, C. Lv, J. Zhou, and Q. Zhang, “Characteristics analysis and fuzzy fractional-order PID parameter optimization for primary frequency modulation of a pumped storage unit based on a multi-objective gravitational search algorithm,” Energies, vol. 13, no. 1, 2019, doi: 10.3390/en13010137.
O. Castillo, F. Valdez, J. Soria, L. Amador-Angulo, P. Ochoa, and C. Peraza, “Comparative study in fuzzy controller optimization using bee colony, differential evolution, and harmony search algorithms,” Algorithms, vol. 12, no. 1, 2019, doi: 10.3390/a12010009.
A. Mughees and S. A. Mohsin, “Design and Control of Magnetic Levitation System by Optimizing Fractional Order PID Controller Using Ant Colony Optimization Algorithm,” IEEE Access, vol. 8, pp. 116704–116723, 2020, doi: 10.1109/ACCESS.2020.3004025.
M. Rabah, A. Rohan, Y. J. Han, and S. H. Kim, “Design of fuzzy-PID controller for quadcopter trajectory-tracking,” Int. J. Fuzzy Log. Intell. Syst., vol. 18, no. 3, pp. 204–213, 2018, doi: 10.5391/IJFIS.2018.18.3.204.
Z. Zhang, L. Tang, W. Hao, and Q. Yuan, “Differential power steering control for in-wheel motored electric vehicle based on variable universe fuzzy PID,” J. Automot. Saf. Energy, vol. 10, no. 2, pp. 169–177, 2019, doi: 10.3969/j.issn.1674-8484.2019.02.004.
R. E. Precup et al., “Model-based fuzzy control results for networked control systems,” Reports Mech. Eng., vol. 1, no. 1, pp. 10–25, 2020, doi: 10.31181/rme200101010p.
O. Domansky, R. Sotner, L. Langhammer, J. Jerabek, C. Psychalinos, and G. Tsirimokou, “Practical Design of RC Approximants of Constant Phase Elements and Their Implementation in Fractional-Order PID Regulators Using CMOS Voltage Differencing Current Conveyors,” Circuits, Syst. Signal Process., vol. 38, no. 4, pp. 1520–1546, 2019, doi: 10.1007/s00034-018-0944-z.
X. Ding, R. Li, Y. Cheng, Q. Liu, and J. Liu, “Design of and research into a multiple-fuzzy pid suspension control system based on road recognition,” Processes, vol. 9, no. 12, 2021, doi: 10.3390/pr9122190.
S. Kapoulea, V. Bizonis, P. Bertsias, C. Psychalinos, A. Elwakil, and I. Petráš, “Reduced active components count electronically adjustable fractional-order controllers: Two design examples,” Electron., vol. 9, no. 1, 2020, doi: 10.3390/electronics9010063.
J. Zhang, C. Li, Q. Jia, and R. Gao, “Research on the Adaptive PID Speed Control Method for Hub Motors,” Mob. Inf. Syst., vol. 2022, 2022, doi: 10.1155/2022/4979824.
C. Sun, Z. Deng, W. Chu, S. Li, and D. Cao, “Acclimatizing the Operational Design Domain for Autonomous Driving Systems,” IEEE Intell. Transp. Syst. Mag., vol. 14, no. 2, pp. 10–24, 2022, doi: 10.1109/MITS.2021.3070651.
S. Barakat, A. I. Osman, E. Tag-Eldin, A. A. Telba, H. M. Abdel Mageed, and M. M. Samy, “Achieving green mobility: Multi-objective optimization for sustainable electric vehicle charging,” Energy Strateg. Rev., vol. 53, p. 101351, 2024, doi: 10.1016/j.esr.2024.101351.
DOI: https://doi.org/10.18196/jrc.v5i6.22071
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Mohamed Shamseldin, Medhat Araby, Samah El-khatib
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Journal of Robotics and Control (JRC)
P-ISSN: 2715-5056 || E-ISSN: 2715-5072
Organized by Peneliti Teknologi Teknik Indonesia
Published by Universitas Muhammadiyah Yogyakarta in collaboration with Peneliti Teknologi Teknik Indonesia, Indonesia and the Department of Electrical Engineering
Website: http://journal.umy.ac.id/index.php/jrc
Email: jrcofumy@gmail.com