Prototype Design Remote Smart Car 4WD Robot Car with Additional Power Photovoltaic Source Integrated Arduino

Muhammad Aldhi; Habib Satria; Moranain Mungkin; Indri Dayana; Rudi Salam

doi:10.46923/ijets.v6i1.291

Muhammad Aldhi Universitas Medan Area, Indonesia
Habib Satria Universitas Medan Area, Indonesia
Moranain Mungkin Universitas Medan Area, Indonesia
Indri Dayana Universitas Medan Area, Indonesia
Rudi Salam Universiti Brunei Darussalam, Brunei Darussalam

DOI: https://doi.org/10.46923/ijets.v6i1.291

Keywords: Robot Car Prototype, Power Photovoltaic Source, Arduino Uno

Abstract

The problem addressed in this research is designing an Electric Car Prototype, a technology design using Arduino Uno, L298N Driver Module, and HC-06 Bluetooth sensor which is controlled automatically using an application. The method used is a hybrid PLTS (Solar Power Plant) system based on Arduino Uno. This prototype combines electrical energy from batteries with solar energy produced by solar panels, and the main controller is Arduino Uno. Tests were carried out to evaluate the performance and efficiency of this electric car. The results of solar panel experiments in designing electric car prototypes, testing will be carried out on the efficiency of solar panels on the power produced. The following is the data from the experimental results measured through the following table 2 experiments. solar panels were installed on the roof or other parts exposed to sunlight on a prototype electric car. Solar panels consist of photovoltaic solar cells which are capable of converting solar energy into electrical energy. When sunlight falls on a solar panel, the solar cell produces an electric current. The electric current generated from the solar cell is then channeled to the charging module to charge the battery. The battery charging module regulates the voltage and electric current according to battery charging needs. This is important so that the battery does not receive too much or too little power during the charging process. After passing through the battery charging module, the electrical energy from the solar panels is used to charge the electric car battery. Electric car batteries function as energy storage which is used to control the engine and other electronic systems in the car. Obtained were the development of an environmentally friendly and sustainable electric vehicle.

References

J. Huang, S. Junginger, H. Liu, and K. Thurow, “Indoor Positioning Systems of Mobile Robots: A Review,” Robotics, vol. 12, no. 2. 2023.

M. F. R. Lee and S. H. Yusuf, “Mobile Robot Navigation Using Deep Reinforcement Learning,” Processes, vol. 10, no. 12, 2022.

H. Qin, S. Shao, T. Wang, X. Yu, Y. Jiang, and Z. Cao, “Review of Autonomous Path Planning Algorithms for Mobile Robots,” Drones, vol. 7, no. 3. 2023.

M. A. K. Niloy et al., “Critical Design and Control Issues of Indoor Autonomous Mobile Robots: A Review,” IEEE Access, vol. 9, 2021.

H. Y. Zhang, W. M. Lin, and A. X. Chen, “Path planning for the mobile robot: A review,” Symmetry (Basel)., vol. 10, no. 10, 2018.

M. B. Alatise and G. P. Hancke, “A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods,” IEEE Access, vol. 8. 2020.

H. Satria, R. Syah, N. A. Silviana, and Syafii, “Sensitivity of solar panel energy conversion at sunrise and sunset on three weather fluctuations in equatorial climate,” Int. J. Electr. Comput. Eng., vol. 13, no. 3, 2023.

P. K. Panigrahi and S. K. Bisoy, “Localization strategies for autonomous mobile robots: A review,” Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 8. 2022.

N. Akai, “Reliable Monte Carlo localization for mobile robots,” J. F. Robot., vol. 40, no. 3, 2023.

H. Satria, S. Syafii, and A. Aswardi, “Analysis of Peak Power Capacity on Rooftop Solar PV 1.25 kWp at Sun Conditions 90 Degrees,” Int. J. Electr. Energy Power Syst. Eng., vol. 4, no. 3, 2021.

M. Russo and M. Ceccarelli, “Survey on mechanical solutions for hybrid mobile robots,” Robotics, vol. 9, no. 2, 2020.

H. Sun, W. Zhang, R. Yu, and Y. Zhang, “Motion Planning for Mobile Robots - Focusing on Deep Reinforcement Learning: A Systematic Review,” IEEE Access, vol. 9. 2021.

H. Satria, M. Mual Gunawan Lubis, and S. Muthia Putri, “Design of Household Electricity Protection and Monitoring Automation With IoT ESP32,” Andalasian Int. J. Appl. Sci. Eng. Technol., vol. 2, no. 03, 2022.

M. M. Rashid, M. M. Rahman, M. R. Islam, O. N. Alwahedy, and A. Abdullahi, “Autonomous 4WD Smart Car Parallel Self-Parking System by Using Fuzzy Logic Controller,” Am. Int. J. Sci. Eng. Res., vol. 2, no. 2, pp. 1–31, 2019.

R. Nie, “Design of Multifunctional Intelligent Car Based on Bluetooth Remote Control,” no. Mmebc, pp. 855–858, 2016.

J. Tao, X. Wang, and J. Si, “Design and Implementation of 4WD Intelligent Car System Based on Integrated Navigation,” Innov. Sci. Technol., vol. 2, no. 3, pp. 41–46, 2023.

W. K. Meteab, H. T. S. ALRikabi, S. A. H. Al Sultani, and I. A. Aljazaery, “Controlling and Monitoring a Robot-Car Based on Smart Phone Applications,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1094, no. 1, p. 012096, 2021.

M. Wada, “Mechanism and control of a 4WD robotic platform for omnidirectional wheelchairs,” 2009 IEEE/RSJ Int. Conf. Intell. Robot. Syst. IROS 2009, pp. 4855–4862, 2009.

N. A. K. Zghair and A. S. Al-Araji, “A one decade survey of autonomous mobile robot systems,” International Journal of Electrical and Computer Engineering, vol. 11, no. 6. 2021.

C. Montero et al., “Modeling and torque control for a 4-wheel-drive electric vehicle,” Proc. IEEE Int. Conf. Ind. Technol., vol. 2015-June, no. June, pp. 2650–2655, 2015.

P. Hang and X. Chen, “Towards autonomous driving: Review and perspectives on configuration and control of four-wheel independent drive/steering electric vehicles,” Actuators, vol. 10, no. 8, 2021.

F. M. Pereira, “5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed Instituto Superior de Engenharia do Porto 5G-Enabled Autonomous Platooning on Robotic Vehicle Testbed,” 2023.

L. Liu, X. Wang, X. Yang, H. Liu, J. Li, and P. Wang, “Path planning techniques for mobile robots: Review and prospect,” Expert Systems with Applications, vol. 227. 2023.

K. Zhu and T. Zhang, “Deep reinforcement learning based mobile robot navigation: A review,” Tsinghua Sci. Technol., vol. 26, no. 5, 2021.