Final Project: Electric Rickshaw modelling

Final Project: Electric Rickshaw modelling

Create a detailed MATLAB model of an electric rickshaw (three wheel passenger vehicle) as per details below: 

Rear wheels driven by PM brushed type motor

Assume efficiency points of motor controller and motor

Make an excel sheet of all input and assumed data 

Results: For any three standard driving cycles show energy consumption, temperature rise of motor and controller for 100 km constant speed driving at 45 kmph.

(Note- The simulink model file should be compulsorily attached)

_______________________________________________________________________

The design of an electric rickshaw for use in India, identifying weaknesses in the current cycle rickshaw, developing a design solution to address problems found, and exploring the possibility of utilizing rechargeable batteries or renewable energy. Through research and testing it was found there were many design issues, and concerns with health and safety, comfort, and ergonomics. All problems found were addressed by implementing design upgrades. The testing of the current cycle rickshaw identified the power and energy required to implement an electric drive system, where a 6 kW 110 V DC motor and a battery capacity of 120-ampere hours were used to provide a range of up to 100 km with a common speed of 45kmph and monitoring the temperatures of Motor and controller.

DESIGN AND MODELLING: -

These rickshaws have an MS (Mild Steel) tubular chassis consisting of three wheels with a differential mechanism at the rear wheels. The motor is a brushless DC motor manufactured mostly in India and China. The electrical system used in the Indian version is 48V and in Bangladesh is 60V The body design from the most popular Chinese version is of very thin iron or aluminum sheets. Vehicles made in fiber are also popular because of their strength and durability, resulting in low maintenance, especially in India.

Here basically, the e-rickshaw is designed in CREO and MATLAB Simulink In the designed electric rickshaw main blocks are battery, drive cycle, controlled, DC Motor, Vehicle body, and transmission system. Drive cycle is the input of human effort that how he is going to drive his actual cycle We can use dive cycle like FTP75, NEDC, or using Spreadsheet.

Block Diagram for the e-rickshaw design as shown below.

MATLAB Simulink model of the E-Auto Rickshaw as shown below

The current flow to the DC motor from the battery through the controller to drive the motor. The required voltage will be controlled in the controller. The controller will follow the commands of the drive cycle reference and run the motor at the required rpm. Then the motor power is transmitted to the wheels of a vehicle through the gearbox and the controller will take the vehicle speed as feedback and it will be compared and controlled.

1. Vehicle Body of Auto Rickshaw

The auto-rickshaw consists of 3 Wheels (1 Front & 2 rear) so that the Magic tire formula blocks were connected to the vehicle body in a fashion of the ‘NF’ connected to the ‘N’ of the front tire and ‘NR’ connected to the ‘N’ Rear tires.

The axle ‘A’ of the rear tires is connected to the simple gear through the differential and the A of the front tire is connected to the ‘Rotational Free End’ because the rear wheels drive the vehicle.

The Hub ‘H’ of the 3 tries was connected to the ‘H’ of the body. The ‘V’ port will be the output that will give the velocity of the vehicle. The ‘S’-port will be connected to the terminator since here we are not considering the slip of the tires.

PS-Simulink converter which will convert the physical signal to simulation data, so that we used as per the requirement of the connections.

The simple gear will connect to the DC motor.

Distance traveled the calculated by formulating the velocity with respective time by using the integrator as shown in the above picture.

The Assumption data of the vehicle body is given below and the remaining parameters consider default

Vehicle Body
Mass(kg)	800
Number of wheels per axle	2
Frontal area(sq.m)	3.4
Drag coefficient	0.25
Air density(kg/m^3)	1.18
Magic Tire Formula
Rolling radius(m)	0.22

The gear ratio of simple gear and the Differential is 4.

2. MOTOR AND CONTROLLER

The electrical connection of the Motor is given through the current sensor which is connected to the controller (H-Bridge). Measure the temperature of the motor and controller enables the Thermal port of both blocks.

The Motor block represents the electrical and torque characteristics of a DC motor including a Thermal port to sense the temperature of the Motor.

The block assumes that no electromagnetic energy is lost, and hence the back-emf and torque constants have the same numerical value when in SI units. Motor parameters can either be specified directly or derived from the no-load speed and stall torque. If no information is available on armature inductance, this parameter can be set to some small non-zero value.

When a positive current flow from the electrical + to - ports, a positive torque acts from the mechanical C to R ports. Motor torque direction can be changed by altering the sign of the back-emf or torque constants.                                    

The Motor Parameter data are given below

Motor Block
Armature Inductance(H)	1.20E-05
No-load speed(rpm)	9500
Rated speed (rpm)	8500
Rated load(W)	6000
Rated DC supply voltage (V)	110
Rotor Inertia (g*cm^2)	0.01
Thermal Mass(J/K)	10000
Initial Temperature (degC)	25

The controller will get input from the driver. Its tasks are to control the speed of the motor and drive according to the input of the driver. Majorly motor controlled we designed two main parts named PWM voltage generator and H-Bridge.

The acceleration command of a driver is given to a controlled voltage source block where it is input to the controlled PWM voltage. Controlled PWM voltage will generate a PWM signal in such a way that H-bridge will generate the required voltage to operate the DC motor for the given driver input. PWM voltage block negative reference and REF are grounded and REF of H-bridge respectively. H-bridge is a motor controller that has IGBT components aligned in the shape of H and will operate only two at a time respectively to the input of the signal from the PWM block. When deceleration occurs this H-bridge will give an output from the positive and negative terminals of it. These negative & positive terminals are later connected to the DC motor and battery. All these components are the Simscape electrical components so they need a connection to the solver configuration block which helps to solve the simulation.

H-bridge motor drive, driven by the Controlled PWM Voltage block in PWM or Averaged mode. In PWM mode, the motor is powered if the PWM port voltage is above the Enable threshold voltage. In Averaged mode, the PWM port voltage divided by the PWM signal amplitude parameter defines the ratio of the on-time to the PWM period. Using this ratio and assumptions about the load, the block applies an average voltage to the load that achieves the correct average load current. The Simulation mode parameter value must be the same for the Controlled PWM Voltage and H-Bridge blocks.

If the REV port voltage is greater than the Reverse threshold voltage, then the output voltage polarity is reversed. If the BRK port voltage is greater than the Braking threshold voltage, then the output terminals are short-circuited via one bridge arm in series with the parallel combination of a second bridge arm and a freewheeling diode. Voltages at ports PWM, REV, and BRK are defined relative to the REF port.

If exposing the power supply connections, the block only supports PWM mode.

H-Bridge
Enable threshold voltage(V)	0.0001
PWM signal amplitude(V)	1
Reverse threshold voltage(V)	0.0001
Braking threshold voltage(V)	0.0001
O/P Voltage Amplitude(V)	110
Thermal Mass(J/K)	10000
Initial Temperature (degC)	25
Controlled PMW Voltage
PMW Frequency(Hz)	4500
Duty cycle Range (V)	0 to 1

3. TEMPERATURE SENSOR

The Temperature Sensor block represents an ideal temperature sensor, that is, a device that determines the temperature differential measured between two points without drawing any heat.

Connections A and B are thermal conserving ports that connect to the two points where the temperature is being monitored. Port T is a physical signal port that outputs the temperature differential value.

The block positive direction is from port A to port B. The measured temperature is determined as T = TA – TB.

Ports

• A-Thermal conserving port associated with the sensor positive probe.
• B-Thermal conserving port associated with the sensor negative probe.
• T-Physical signal output port for temperature.

The Thermal port of the Motor and controller is connected to the Temperature sensors of its individuals and the output port ‘T’ of both sensors is given to a Bus creator block, the output will give to the scope that will combine the outputs and will provide proper visualization of the Temperatures of both in scope.

4. BATTERY

The battery block got connected to the motor through a controlled current source in series. Here we can get the State of charge, current, and voltage drawn by the battery so that we can calculate the energy consumed by the battery.

The assumption data of the battery

Battery Bank
Nominal voltage (V)	110
Rated capacity (Ah)	120
Initial state-of-charge (%)	100
Battery response time (s)	30

5. DRIVER AND DRIVE INPUT

The Longitudinal Driver block implements a longitudinal speed-tracking controller. Based on reference and feedback velocities, the block generates normalized acceleration and braking commands that can vary from 0 through 1. You can use the block to model the dynamic response of a driver or to generate the commands necessary to track a longitudinal drive cycle.

Used the Proportional-integral (PI) control with tracking windup and feed-forward gains with default gain values.

The Acceleration and Braking/Deceleration commands are given by the driver to the motor controller. In the simulation, the driver gets the input commands with the help of Drive cycles.

A driving cycle is a series of data points representing the speed of a vehicle versus time. Driving cycles are produced by different countries and organizations to assess the performance of vehicles in various ways, such as for instance fuel consumption, electric vehicle autonomy, and polluting emissions.

We have taken 3 drive cycle inputs for simulation which were FTP75, NEDC, and Drive cycle data through a spreadsheet.

FTP75: -

The EPA Federal Test Procedure, commonly known as FTP-75 for the city driving cycle, is a series of tests defined by the US Environmental Protection Agency (EPA) to measure tailpipe emissions and fuel economy of passenger cars (excluding light trucks and heavy-duty vehicles).

Then the characteristics of the cycle are:

• Distance traveled: 11.04 miles (17.77 km)
• Duration: 1874 seconds
• Average speed: 21.2 mph (34.1 km/h)

NEDC: -

The New European Driving Cycle (NEDC) is a driving cycle, designed to assess the emission levels of car engines and fuel economy in passenger cars (which excludes light trucks and commercial vehicles). It is also referred to as the MVEG cycle (Motor Vehicle Emissions Group).

Characteristics of NEDC

• Average driving speed (excl. stops) km/h:   10
• Maximum speed km/h: 120
• Average acceleration1 m/s2: 506

Spreadsheet Drive cycle: -

The drive cycle data was prepared for 13200 sec of the time period and the most common speed the 45kmph for 4781 secs, the maximum speed of 55 kmph for 393secs in overall drive cycle data. The max distance can travel of 125.1km.

All these drive inputs are given to the driver through the multiport switch which can we can change the input by changing the value in the constant block (Selector).

RESULTS

DRIVE Input: FTP75

 The simulation period of 2474sec for this drive cycle, the drive input vs vehicle speed plot shown below.

The maximum speed of the given drive input is 91kmph, but we can see that the vehicle achieved a maximum speed of 46kmph with the designed motor and its controller.

The total distance covered:14.97km

We can see the 5 sec lag by the vehicle speed for the given input when the vehicle changed from deceleration or braking mode to acceleration mode. This delay is based on the controller PI gains and the load of the vehicle.

The SOC and the energy consumption of the vehicle to travel by the given drive input as shown below

The SOC battery is from 100% to 93.4%, we can see some ups in the graph which means that while the vehicle is in deceleration or braking mode motor acting as a generator will generate the power since the controller was regenerative, Battery will get charged. With respect to that, we can see the voltage and current drawn from the battery while discharging and charging as shown below.

The overall energy consumed by the vehicle is that 0.93kWh.

The Heat generated by the motor and the controller is shown below.

From the initial temperatures (298 K) of the Motor and the controller, we can see that the motor temperatures rise gradually and reached (361 K) but the Temperature of the controller rises rapidly in the whole simulation from an initial temperature of 293 K to 452K.

In real-time, the temperatures won’t rise like this because the cooling systems were installed at the locations to avoid overheating and getting damaged.

DRIVE Input: NEDC

The simulation period of 1180sec for this drive cycle, the drive input vs vehicle speed plot shown below.

The maximum speed of the given drive input is 120kmph, but we can see that the vehicle achieved a maximum speed of 46kmph with the designed motor and its controller.

The total distance covered:8.354km

Here are also 5-sec lags by the vehicle speed for the given input when the vehicle changed from deceleration or braking mode to acceleration mode. This delay is based on the controller PI gains and the load of the vehicle.

The SOC and the energy consumption of the vehicle to travel by the given drive input as shown below

The SOC battery is from 100% to 96.5%, we can see some ups in the graph which means that while the vehicle is in deceleration or braking mode motor acting as a generator will generate the power since the controller was regenerative, Battery will get charged. With respect to that, we can see the voltage and current drawn from the battery while discharging and charging as shown below.

The overall energy consumed by the vehicle is 0.535kWh.

The Heat generated by the motor and the controller is shown below.

From the initial temperatures (298 K) of the Motor and the controller, we can see that the motor temperatures rise gradually and reached (317 K) but the Temperature of the controller rises rapidly in the whole simulation from an initial temperature of 293 K to 336.5K.

In real-time, the temperatures won’t rise like this because the cooling systems were installed at the locations to avoid overheating and getting damaged.

DRIVE Input: Spreadsheet DATA

Since we have an objective of achieving a 100 km travel distance with the most constant speed of 45 kmph the simulation period of 10500sec for this drive cycle, the drive input vs vehicle speed plot is shown below.

The maximum speed of the given drive input is 55kmph, but we can see that the vehicle achieved a maximum speed of 45kmph with the designed motor and its controller.

The total distance covered:100.1km

Here 8-sec lags by the vehicle speed for the given input when the vehicle changed from deceleration or braking mode to acceleration mode. This delay is based on the controller PI gains and the load of the vehicle.

The SOC and the energy consumption of the vehicle to travel by the given drive input as shown below

The SOC battery is from 100% to 59.7%, we can see some ups in the graph which means that while the vehicle is in deceleration or braking mode motor acting as a generator will generate the power since the controller was regenerative, Battery will get charged. With respect to that, we can see the voltage and current drawn from the battery while discharging and charging as shown below.

The overall energy consumed by the vehicle is 5.87kWh.

The Heat generated by the motor and the controller is shown below.

From the initial temperatures (298 K) of the Motor and the controller, we can see that the motor temperatures rise gradually and reached (400 K) but the Temperature of the controller rises rapidly in the whole simulation from an initial temperature of 293 K to 587.5K. These heavy temperatures will burn the devices.

In real-time, the temperatures won’t rise like this because the cooling systems were installed at the locations to avoid overheating and getting damaged.

Conclusion:

• Created a MATLAB Simulink model of an Electric Auto Rickshaw (three-wheel passenger vehicle) by using a Li-ion battery, PM Brushed DC Motor.
• Determined the variations of Temperature of Motor and controller, SoC% and Energy consumed by the vehicle for all the three Reference Drive cycles (i.e.; FTP75, NEDC, and Manually prepared Spreadsheet).
• In this design, we have compromised the temperature of the Motor and controller to achieve vehicle speed near reference speeds. Since I haven’t used any cooling system in the model. In a real-time application, the motor temperature is less than 358 K.
• In the real-time application, the motor, battery & controller temperature is controlled by air cooling. Hence, the temperature of the components won’t increase to extreme numbers.