Design and Fabrication of Autonomous Tracked Electrical Vehicle

Project Title

Design and Fabrication of Autonomous Tracked Electrical Vehicle

Project Area of Specialization Artificial IntelligenceProject Summary

We aim at designing a small, safe and smart locomotive for transportation inside organizations. Following are the modules on which we are working.

• Efficient speed and direction control of Geared Brushed DC motor with motor driver rated for 30kg of weight.
• Using Arduino as slave sensor to connect motors drivers and motors.
• Use of sensor i.e. SONARS for changing the speed by puulse width modulation (PWM) technique.
• Use of IR sensors to keep the Autonmous Electric Car on track , i.e. Path following technique.
•  Machine learning for efficient obstacle detection and braking system of car ahs been employes.
• The controller used is Rasberry pi 4 which will take real time input in the form of video (fps), whatever is the obstacle will be detected and decision will be taken in accordance with the the object. If the human is detected the alarm will go off. And if the animal aor a bigger hurdle comes in front of the car , the brakes will be applied.
• The Electric Power is supplied from the solar energy for which the solar panels willl using MPPT or Maximum Power Point Tracking  algorithm that includes in charge controllers used for extracting maximum available power from PV module.
• IoT Technique is being used to shut of the power supply from battery once the battery is 99.0 % charged.
• The wheels and bearings design is in accordance with the weight whole symmetry is bearing.
• Li-ion DC Battery is used as an Alternate source.
• The E-Vehicle is designed to follow the straight path using Machine learning techniques (using trained models)
• Lastly, all the data from sensors will be transferred using Wi-fi modules on Apps , which can also remotely control the vehicles' actions. 

Project Objectives

• Design and Fabrication of Autonomous Tracked Electric Vehicle System.
• Design and implementation of a small, safe and smart locomotive for transportation inside the University of Engineering & Technology, Taxila.
• Efficient speed and direction control of DC motors.
• Use of IR & Sonar sensors to detect the obstacle and change the speed of motor accordingly.
• Employing Machine learning techniques for processing images and for Braking of car.

Project Implementation Method

• The drivers rating were selected in accordance with weight car has  bear.
• IBT2 motor driver and the geared Brushed DC motors are used.
• The DC brush motor is used beacuse the supply is from DC battery which is being powered from Solar energy.
• The SONARs are used in parabolic shape to broaden the view from 180 degree to 185 degree, the SONARS are used for changing the pWM and eventually the speed of Motor.
• The IR sensors are used to keep keep the car on track and also to control the speed. they are installed just near the tyre or wheel of car, when the shadow of another obstacle will fall , the signals being sent to arduino which will furthur control motors.
• Machine Learning is used to detect the obstacles in front of car, to detect the traffic signs and signals, human & animals.
• The pi-cam is used as a sensor to take the video's frame per seconds and then input is being sent to classifier.
• The rasberrry pi 4 is used as a controller to detect objects and take decisions of cars' motion.
• The language used is python for programming of rasberry pi 4, 
• IoT technique is being used for SENSORS FUSION , Iit will interface all the sensors data through wifi modules.
• The rasberry pi will be used as Masters Controller and Arduino Uno will be the slave controlling Motors.

Benefits of the Project

• Automated cars can reduce non-renewable energy consumption in transportation up to 90%. Because no gasoline (petrol) or gas (CNG) is being used . The only source is electricity and vehicle is being powered by solar energy. Also the efficiency will be 95% by using MPPT Technique.
• Self-driving car can move faster and it's battery timing hour can run the car fo 8 hours.
• E-car is more safe than a car driven by a human, which decreases traffic congestion.
• The number of car crashes will most certainly fall with self-driving cars, the production of safety equipment and vehicle testing should decrease as well.
• Autonomous vehicles are also programmed to operate in a more fuel-efficient manner and self-driving trucks and cars can be programmed to operate at maximum efficiency all the time.
• Autonomous cars use significantly less gas and energy when driving, compared to a vehicle driven by a human.
• Most gas is burned when driving at high speeds, braking, and re-accelerating excessively.
• Self-driving vehicles cut these factors out of their driving style, meaning less gas is burned, or battery power consumed, resulting in less air pollution.
• riverless car technology is advanced, the weight of the cars will drop as a result of lighter batteries, and less need for heavy safety modifications to the engine.

Technical Details of Final Deliverable

• The motors drivers rating were selected in accordance with weight car has  bear.
• IBT2 motor driver is used with following specifications.The BTS7960 is a fully integrated high current H bridge module for motor drive applications. Interfacing to a microcontroller is made easy by the integrated driver IC which features logic level inputs, diagnosis with current sense, slew rate adjustment, dead time generation and protection against overtemperature, overvoltage, undervoltage, overcurrent and short circuit. The BTS7960 provides a cost optimized solution for protected high current PWM motor drives with very low board space consumption.
  • Input voltage : 6V-27V
  • Maximum Current : 43A
  • Input level : 3.3V-5V
• The geared Brushed DC motors are used.
• The DC brush motor is used beacuse the supply is from DC battery which is being powered from Solar energy.It has following specifications.A gear motor is an all-in-one combination of a motor and gearbox. The addition of a gear head to a motor reduces the speed while increasing the torque output. 
• The SONARs are used in parabolic shape to broaden the view from 180 degree to 185 degree, the SONARS are used for changing the pWM and eventually the speed of Motor.
• The IR sensors are used to keep keep the car on track and also to control the speed. they are installed just near the tyre or wheel of car, when the shadow of another obstacle will fall , the signals being sent to arduino which will furthur control motors.
• Machine Learning is used to detect the obstacles in front of car, to detect the traffic signs and signals, human & animals.
• The pi-cam is used as a sensor to take the video's frame per seconds and then input is being sent to classifier.
• The rasberrry pi 4 is used as a controller to detect objects and take decisions of cars' motion.
• The language used is python for programming of rasberry pi 4, 
• IoT technique is being used for SENSORS FUSION , Iit will interface all the sensors data through wifi modules.
• The rasberry pi will be used as Masters Controller and Arduino Uno will be the slave controlling Motors.

Final Deliverable of the Project HW/SW integrated systemCore Industry TransportationOther Industries Energy , Others Core Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT), RoboticsSustainable Development Goals Good Health and Well-Being for People, Affordable and Clean Energy, Industry, Innovation and Infrastructure, Responsible Consumption and Production, Climate ActionRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	61000
raspberry pi 4	Equipment	1	15000	15000
arduino	Equipment	2	1300	2600
SONAR	Equipment	15	150	2250
IR	Equipment	15	150	2250
IBT 2	Equipment	2	1700	3400
brushed DC motor	Equipment	2	8000	16000
Solar Panel	Equipment	1	15000	15000
pi-cam 8 Mega pixel	Equipment	1	3000	3000
SD-Card	Equipment	1	1500	1500