Final Project: Electric Rickshaw modelling

Aim :-

Design of Electric rickshaw three wheeler

Objective :-

Creating a electric rickshaw rear wheel drive by the assuming the data by ourselves and make a excel sheet data.

Introduction :-

An electric rickshaw, also known as an e-rickshaw or electric three-wheeler, is a type of vehicle that runs on electricity and has three wheels instead of the typical four wheels found in most cars. These vehicles are commonly used as taxis and for short-distance transportation in cities and towns in many countries, especially in South and Southeast Asia.

A rare wheel drive electric rickshaw has one wheel in the front and two wheels at the rear, with the motor powering the two rear wheels. The front wheel is usually for steering purposes and does not provide power to move the vehicle.

The working of an electric rickshaw with rare wheel drive can be explained as follows:

Power Source: The electric rickshaw is powered by an electric motor that runs on rechargeable batteries. The batteries are usually lead-acid or lithium-ion batteries, which are charged using an external charging device.

Acceleration: The motor is connected to the rear wheels via a transmission system. When the driver presses the accelerator pedal, the motor provides power to the wheels, which results in the vehicle moving forward.

Steering: The driver steers the electric rickshaw using the handlebar, which is connected to the front wheel. The front wheel turns in the direction the driver steers, allowing the vehicle to change direction.

Braking: The electric rickshaw is equipped with a hydraulic or mechanical braking system that helps to slow down or stop the vehicle when required.

Control: The driver has access to various controls, such as the accelerator pedal, brake pedal, and the horn, which are mounted on the handlebar for easy access.

Overall, the rare wheel drive electric rickshaw provides an efficient and eco-friendly mode of transportation for short distances, and its simple construction and low maintenance requirements make it a popular choice in many parts of the world.

Designing parts :-

(a) Drive Cycle

(b) PID Controller

(c) Motor controller

(d) Vehicle Body subsystem

(e) Battery and soc subsystem

(a) Drive Cycle :-

Drive Cycle :-

A drive cycle involves a sequence of driving conditions that include a mix of urban and highway driving, different speeds, accelerations, and decelerations. The cycle may also include idling, hot and cold starts, and other variables that affect emissions and fuel consumption.

Drive cycles are used to evaluate the performance and emissions of vehicles, as well as to develop and calibrate onboard diagnostic systems (OBD) that monitor and control emissions in real-world driving conditions. They are also used to establish regulations and standards for vehicle emissions and fuel economy and here I use FTP75.

(b) Longitudinal Driver :-

A PID (Proportional-Integral-Derivative) controller is a type of feedback control system commonly used in industrial and engineering applications to regulate a process. The controller receives a measurement of the process variable, compares it to a desired setpoint, and calculates an error signal. The error signal is then used to adjust the control input to the process in order to reduce the error and bring the process variable closer to the setpoint.

The three components of a PID controller are:

Proportional (P) term: This term produces an output that is proportional to the current error signal. The gain of the P term, denoted as Kp, determines the strength of the response to the error signal.

Integral (I) term: This term produces an output that is proportional to the integral of the error signal over time. The I term helps to eliminate steady-state error and improve the system's response to slow changes in the error signal. The gain of the I term, denoted as Ki, determines the responsiveness of the controller to the error signal over time.

Derivative (D) term: This term produces an output that is proportional to the rate of change of the error signal. The D term helps to improve the system's response to rapid changes in the error signal and prevent overshoot. The gain of the D term, denoted as Kd, determines the responsiveness of the controller to the rate of change of the error signal.

The output of the PID controller is the sum of the three terms:

Output = Kp * Error + Ki * Integral(Error) + Kd * Derivative(Error)

Where Error is the difference between the setpoint and the process variable, and Integral(Error) and Derivative(Error) are the integral and derivative of the error signal, respectively.

By adjusting the gains of the P, I, and D terms, a PID controller can be tuned to achieve a desired response to changes in the error signal and maintain stable control of the process variable

Designing a PID controller involves the following steps:

Determine the system transfer function:

The transfer function relates the output of the system to its input. This can be obtained through experiments or simulations. It is typically expressed in terms of Laplace transforms.

Choose a performance criterion:

This could be steady-state error, rise time, settling time, overshoot, or a combination of these.

Choose a control strategy:

This could be a P controller, PI controller, PID controller, or another type of controller.

Choose initial controller parameters:

For a PID controller, this would be the proportional gain (Kp), integral gain (Ki), and derivative gain (Kd). The initial values for these parameters can be based on experience, tuning rules, or trial and error.

Simulate or test the controller:

Simulate or test the system with the chosen controller and observe the performance. If the performance criterion is not met, adjust the controller parameters and repeat the process until the desired performance is achieved.

Implement the controller:

Implement the final controller in the system and monitor its performance to ensure it is meeting the desired performance criteria.

There are various methods to tune a PID controller, including manual tuning, Ziegler-Nichols method, Cohen-Coon method, and others. However, the basic approach outlined above provides a general framework for designing and tuning a PID controller.

It's worth noting that there are also many software tools available for designing and tuning PID controllers, such as MATLAB's Control System Toolbox, Simulink, and various other third-party software packages. These tools can greatly simplify the process and help to ensure that the controller is properly designed and tuned.

(c) Motor controller

Controlled PWM voltage signal block :-

It generates a Pulse Width Modulation (PWM) waveform with a controllable duty cycle and frequency. The block typically has inputs for the reference signal, which is the desired voltage to be generated, and a modulation index, which determines the amplitude of the PWM waveform. The block also has outputs for the PWM waveform and its complementary signal.

Ports

The PWM & REF connections are for the corresponding ports on the H-Bridge circuit.

The 2 reference inputs correspond to the throttle inputs given by the driver. The block generates corresponding pulse width as per the accelerations and brakes applied by the driver himself.

In this project as PWM frequency signal 3000Hz

Power convertor h-bridge :-

The H-bridge Simulink block typically has inputs for the DC input voltage and a control signal that determines the duty cycle of the output waveform. The block also has outputs for the AC output voltage and current.

The H-bridge circuit consists of four switches arranged in an H-shaped configuration. By turning on and off these switches in a specific sequence, the H-bridge circuit can generate an AC output waveform with a controllable voltage and frequency.

In this project H-bridge take PWM controlled signal from control PWM voltage generator.

Battery charge and discharge :-

To model the Battery pack, a simple Battery block is used. This is because, if the generic battery block is used instead, the simulation will run for a much longer time.

Here, the selected option for Battery Charge Capacity is Finite. Accordingly, the block models the battery as a series internal resistance plus a charge-dependent voltage source.

If the chosen option had been Infinite, the voltage source would have been constant.

Also, the self-discharging of the battery and the battery dynamics are disabled.

Motor (permanent magnet DC) :-

The DC Motor block represents the electrical and torque characteristics of a DC motor using the following equivalent circuit model and its provide mechanical output.

Battery state of charge :-

State of charge (SoC) refers to the amount of electrical energy that is currently stored in a battery or other energy storage system, expressed as a percentage of its total capacity. It indicates how much of the battery's available energy has been used and how much remains. For example, a battery that is fully charged has a SoC of 100%, while a battery that is completely discharged has a SoC of 0%. SoC is an important parameter to monitor when using batteries, as it can affect the battery's performance and lifespan.

SOC = (Q/Qmax) x 100%

Solver Configuration :-

A Solver Configuration is added to ensure proper solving of the mathematical equations by the model.

Vehicle body :-

The block typically has inputs for the external forces and torques acting on the body, such as those from the wheels, suspension, and aerodynamic effects. It also has outputs for the position, velocity, and orientation of the body, which can be used to connect to other blocks in the simulation.

The Vehicle Body block can be useful for simulating vehicle dynamics and evaluating the performance of different suspension and control systems.

This 2 axle (4 wheel) assembly is now connected to a Velocity Body Simscape block.

This block basically represents a two-axle vehicle body in longitudinal motion. The block accounts for -

body mass,

aerodynamic drag,

road incline,

weight distribution between axles due to acceleration

road profile.

Here, the connection H is the mechanical translational conserving port hub.

NF & NR correspond to the output ports for normal reaction forces on front axle and rear axle wheels respectively.

Connection V represents the actual output translational velocity of the vehicle.

beta is the road inclination angle & W corresponds to the headwind speed (headwind - direction opposite to that of vehicle).

And the specified parameters are shown in the pic.

Tire

The wheels are modelled using simple Tire (Magic formula) simulink blocks.

The N port of the tire corresponds to the Normal Reaction acting on it.

The A port corresponds to the Mechanical Rotational conserving port for the wheel axle. Thus both the wheels on the same axle should form a connection through their respective A ports.

Connection H corresponds to the Mechanical Translational conserving port for the wheel hub through which the thrust developed by the tire is applied to the vehicle. Thus, all the 3 wheels form a connection through their respective H ports and this is in turn connected to the translational hub of the vehicle body.

Here in this project engine is mounted in the front of the vehicle and the transmission is located at the rear. In contrast, front-wheel drive (FWD) vehicles typically have a transverse engine layout, which means that the engine is mounted sideways and the transmission is located at the front.