Design of E-Rickshaw by using MATLAB-SIMULINK

 

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.

INTRODUCTION

Electric E-Rickshaw is also known as electric tuk-tuk, e-rickshaw and auto which are going more popular after 2018 in Indian market. This E-rickshaw is best alternative of petrol/ CNG auto rickshaw and human or horse pulled rickshaws because of their low fuel cost, zero emissions and less human efforts.

The electrical system used in Indian version is 48VDC can run 90– 100 km/full charge, top speed 25 km/hour and this electric motor power ranging from 650-1400 Watts; the battery takes 8–10 hrs to become fully charged. Basic seating capacity is driver plus 4 passenger total 5 persons.

Here basically, 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 drive cycle like FTP75, WOT or by using Excel.

The main objective of this project is to obtain speed by driver, to estimate the temperature of motor and controller, to estimate the state of charge (SOC) and distance travel by the vehicle. There is a SOC block that will estimate the state of charge of battery, distance is calculated by speed and time parameter for all the three Drive cycle.

General detail of E-Rickshaw

• Battery Type Lithium Ion 60.8 V 160 Ah
• Vehicle kerb weight 260 kgs
• Load capacity 340 kgs
• Vehicle speed 7 kmph
• Driving range 140 km (160 Ah)
• No of wheels per axel 2
• Frontal Area 91m²
• Drag coefficient 5
• Wheel radius 306m
• Vertical load 3000 N
• Nominal Voltage 8 V
• Rated Capacity 160 Ah
• Initial SOC % 100
• Internal Resistance 5 ohm

A CAD model of Electric rickshaw is shown below.

• Electric Motor: PM brushed DC Motor type 650- 1400W & 48V (Input) motor is used. It is controlled via an electronic controller.
• Electronic Motor Controller: The controller includes a manual or automatic switch turning the motor on/off, selecting forward or reverse motion, selecting and regulating speed, regulating or limiting torque and protecting against overloads. It is connected to battery pack and controller feeds the input to the motor, lamp, AC/DC converter and Speedometer/ Indicator.
• Battery: Set of four 12V deep cycles /Li-ion batteries are used since the required voltage is 48V. These batteries are connected in series to the controller unit.
• Front Shock Absorbers: Helical Spring with dampener with hydraulic telescopic shock absorbers are used.
• Rear Suspension: Leaf spring carriage spring with rear shocker
• Brakes: Drum brakes, actuated internally, expanding shoe type are used. Brakes are mounted on the chassis (Pedal brakes), so on pressing the pedal, the brakes will engage stopping the rear wheels.
• Speedometer/Indicator: Speedometer generally used have analogue dials. The one the left side indicates vehicle speed and one on the right side indicate battery charge level. It is connected to the controller unit.
• Steering: Handle bar type steering is used.
• Miscellaneous Spare parts: Centre locking, Alloy wheel, Rear light, Front glass, Front Indicator, Headlight, Ignition switch, Charger, Converter, left-right switch, Tyre, Wirings, Throttle set etc.

Specification

Basic Dimension of E-Rickshaw (All dimension is in mm)

MATLAB Modelling of e-rickshaw

As we can see that the above diagram is consisting of MATLAB Simulink model of an electric rickshaw. In above model we use three type of different drive cycle to run the vehicle body. A basic current is applied to the model. The required voltage to the vehicle is controlled by the controller. Depending upon the vehicle parameter the controller will follow the drive cycle and run the motor.

Full Model Parameter

Drive cycle

Here I have used three different type of drive cycle which are as given below.

UDDS Drive Cycle

Urban Dynamometer Driving Schedule

HWFET Drive Cycle

Highway Fuel Economy Driving Schedule

FTP Drive cycle

Generate a standard or user specified longitudinal drive cycle.

MODELLING OF VEHICLE BODY SYSTEM:

The above figure highlights the vehicle body for electric rickshaw which is having rear axle drive. The Vehicle Body block represents a two-axle vehicle body in longitudinal motion.

The block consists of body mass, aerodynamic drag, road incline, and weight distribution between axles due to acceleration and road profile. In optionally we can include pitch and suspension dynamics.

In a given block

1. NR: It is a physical signal output which is connected to the rear wheel axel. For this model, it is connected with a normal force of rear tire.
2. NF: It is a physical signal output which is connected to front-wheel axel and for this particular model it is connected with the normal force acting on a front-wheel tire.
3. Beta: Beta is basically a road incline angle. Here we can define a constant value for road angle inclination.
4. H: This port is a horizontal motion of the vehicle body. This connection will be connected with all four Hub of the wheel for finding the thrust generated by the tire.
5. V: This port is the vehicle longitudinal velocity.
6. W: It is a headwind speed. Basically, we will define a particular wind speed by adding constant block.

• For setup of vehicle body just double click on the vehicle body and enter as per requirement.
• Here I have done some changes in vehicle configuration, Basically, I changed the vehicle mass, length and frontal area.

• Detail input of Vehicle Body

Main Settings

1. Mass: 600 Kg
2. Number of wheels per axle: 2
3. The horizontal distance from CG to front axle: 1.2 m
4. The horizontal distance from CG to the rear axle: 1.32 m
5. CG height above ground: 0.5 m
6. Externally-defined additional mass: OFF
7. Gravitational acceleration: 9.81 m/s^2
8. Negative normal force warning: OFF

Drag Settings

1. Frontal area: 1.91 m^2

1. Drag coefficient: 0.19
2. Air density: 1.25 kg/m^3

Pitch Setting

1. Pitch dynamics: OFF

Variable Settings

1. Beginning Value of Velocity: 0 m/s

Other connected detail

• Wind Velocity: 2.22222 m/s
• Road Incline: 0

For calculating the velocity here, we have created a subsystem i.e LOG mph, this block basically consists of PS Simulink converter, Gain, Zero order Hold.

• Gain Block: 1.61 and it multiply input value with constant input.
• Zero-order Hold: 0.01, The Zero-Order Hold block holds its input for the sample period you specify.

TIRE MODELLING

 

The Tire (Magic Formula) block models a tire with longitudinal behaviour given by the Magic Formula, an empirical equation based on four fitting coefficients. The block can model tire dynamics under constant or variable pavement conditions.

The Tire (Magic Formula) block models the tire as a rigid wheel-tire combination in contact with the road and subject to slip. When torque is applied to the wheel axle, the tire pushes on the ground (while subject to contact friction) and transfers the resulting reaction as a force back on the wheel. This action pushes the wheel forward or backwards. If you include the optional tire compliance, the tire also flexibly deforms under load.

The figure shows the forces acting on the tire.

Were,

            Fx = Longitudinal force exerted on the tire at the contact point

            Fz = Vertical load on the tire

            Ω = Wheel angular velocity

            Vx = Wheel hub longitudinal velocity

In the particular block

• N: Normal force acting on the tire and connected with NR of the vehicle body.
• S: Slip between the tire and road and connected with Goto block
• H: Hub and it is used to find the thrust created by the tire and it is connected with H input of vehicle body also including all four Hub of the wheel.
• A: Axel and rear axle are connected with the (Simple Gear) final drive system and the front axle is connected with the left and right wheel.

In Tire block, we can change the parameter

 

Main Settings

• Parameterize by: Load-dependent Magic Formula coefficients, it is basically specifying the parameters that define the load-dependent.
• Tire nominal vertical load – This is basically a normal force on the tire (Fz0). So, for this particular model, the normal force I have taken is 3000 N.
• Magic formula C, D, E, BCD, H and V are default. Basically, It is a load-dependent Magic Formula Coefficient.

Geometry Setting

• Rolling radius: 0.32, it is Unloaded tire-wheel radius, rw

Dynamic Settings

• Inertia: No Inertia

Rolling Resistance Setting

• Rolling resistance: On, Basically, it includes the rolling resistance.
• Resistance model: By using Constant Coefficient we are Neglect rolling resistance.
• Constant coefficient: 0.015 the value should be greater than 0 and it is a coefficient that sets the proportionality between the normal force and the rolling resistance force.
• Velocity threshold: 0.001 m/s basically this input is a velocity at which the full rolling resistance force is transmitted to the rolling hub.

Advance setting

• Velocity threshold: 0.1 m/s as I keep this value as default and this value should be positive because it is wheel hub velocity Vth below which the slip calculation is modified to avoid singular evolution at zero velocity.

INERTIA

This block generally represents the mechanical rotational element.

Where,

            T = Inertia torque

            J = Inertia

            Ω = Angular velocity

            T = Time

So here the inertia value is 0.01 kg×m^2 and this block is connected with rear axle and (Simple Gear) final drive ratio to find the inertia because axel and gear are a mechanical rotating device.

SIMPLE GEAR

Simple Gear is a Final drive ratio which is a gearbox that constrains the connected driveline axes of the base gear and the follower gear.

B: The output B, base gear is connected with the input of DC motor R. It is a Rotational mechanical conserving port.

F: The output of F, follower gear is connected with the rear axle. It is also a Rotational mechanical conserving port.

In Simple Gear Block we can also do some changes according to our need.

Main Setting

• Follower (F) to base (B) teeth ratio (NF/NB): 5, The value should be in Positive and it is a fixed ratio gFB of the follower gear to the base gear.
• Output shaft rotates: In the same direction as the input shaft, it is depending upon the direction of follower and base gear.

Meshing Losses

• Friction model: From drop-down, we can select Constant efficiency which calculates the Reduce torque transfer by a constant efficiency factor.
• Efficiency: 0.86, here we can change the efficiency depending upon our need, basically it is a Torque transfer efficiency between base gear shaft to the follower gear shaft.
• Follower power threshold: 0.001 W, it is an absolute value of the follower shaft power above which the full efficiency factor is in effect.

GOTO

GoTo block is used to display the vehicle speed.

CONFIGURATION BATTERY AND SOC

In given block there are some changes to configure the Lithium battery.

Basically, in battery a special change has done and i.e.

Under Parameter > Lithium-Ion (Change the following data)

• Nominal Voltage = 60.8 (V)
• Rated Capacity = 160 (Ah)

Under Discharge (Change the following data)

• Maximum Capacity = 160 (Ah)
• Cut-off Voltage = 53.2 (V)
• Fully Charged Voltage = 70.3 (V)
• Nominal Discharge Current = 100 (A)
• Internal Resistance = 0.5 (Ohms)
• Capacity at Nominal Voltage = 160 (Ah)

So, at Discharge rate of [51.3 66.8 49.4 70.3] the plot will be

The circuit parameters can be modified to represent a specific battery type and its discharge characteristics. A typical discharge curve consists of three sections.

A basic block configuration and steps involve during whole system analysis.

Block used:

• PowerGUI
• Controlled Current Source
• Battery
• Temperature Ambient (Constant)
• Bus Selector
• Integrator
• Divide
• Product
• Time
• Scope

Controlled Current Source

The Controlled Current Source block converts the Simulink input signal into an equivalent current source. The generated current is driven by the input signal of the block. The positive current direction is as shown by the arrow in the block icon.

We can initialize the Controlled Current Source block with a specific AC or DC current. If we want to start the simulation in steady state, the block input must be connected to a signal starting as a sinusoidal or DC waveform corresponding to the initial values.

• Double click controlled current source and from drop down menu of measurement select current.
• Signal output will connect with scope by adding current signal to it.
• (+) terminal will connect with battery (-) terminal.

Battery

The Battery block implements a generic dynamic model that represents most popular types of rechargeable batteries.

• In battery setup just do the above changes which I highlighted above.
• Just connect ambient temperature with Ta input of battery.
• “M” will be connected with BUS selector lock.

BUS Selector

The Bus Selector block outputs the signals you select from the input bus. The block can output the selected elements separately or in a new virtual bus.

• Here just we have mange the output and connect with different Scope Block.

PowerGUI

The powergui block allows us to choose one of these methods to solve your circuit:

• Continuous, which uses a variable-step solver from Simulink
• Discretization of the electrical system for a solution at fixed time steps
• Continuous or discrete phasor solution

The powergui block also opens tools for steady-state and simulation results analysis and for advanced parameter design.

For calculating the SOC (State of Charge) we have to create a subsystem which will consist of Rate transition, Gain, Discrete Time Integrator, Constant and Sum blocks.

RATE TRANSITION

It is used to transfers data from the output of a block operating at one rate to the input of a block operating at a different rate.

Input Signal: Input signal to transition to a new sample rate, specified as a scalar, vector, matrix, or N-D array.

Output Signal: Output signal is the input signal converted to the sample rate you specify.

A basic input for this block is as

GAIN BLOCK

The Gain block multiplies the input by a constant value (gain). The input and the gain can each be a scalar, vector, or matrix.

Here Gain value is the multiplication element and the input is 1/(50×3600), where 50is battery ampere and 3600 is second.

DISCRETE-TIME INTEGRATOR

The discrete-time integrator block is used for

• Define initial conditions on the block dialogue box or as input to the block
• Define an input gain (K) value
• Output the block state
• Define upper and lower limits on the integral
• Reset the state with an additional reset input

SUM BLOCK

The Sum block performs addition or subtraction on its inputs.

In this block, the negative terminal will be connected with discrete-time integrator and positive terminal with constant.

DC MOTOR WITH TEMPERATURE CALCULATION

The DC Motor block represents the electrical and torque characteristics of a DC motor using the following equivalent circuit model:

Here in this system, the positive terminal is connected with the current sensor negative terminal and negative terminal is connected with the negative terminal of H-Bridge.

R is DC motor rotor which connected with mechanical rotational port i.e. simple gear whereas C is DC motor case and it is connected with mechanical rotational reference.

A basic configuration of the DC motor is as follow:

Here for the particular model, I configure in DC Motor and try to change a basic setting in electrical torque.

• No-load Speed: 5000 rpm, this is the speed of the motor when not driving a load.
• Rated speed (at load): 1500 rpm, this is the speed of the motor at rated mechanical power level.
• Rated load (mechanical Power): 9.72 kW

Another Mechanical detail of DC motor is as follow

• Rotor Inertia: It’s a resistance of the rotor to change in motor motion.
• Rotor Damping: It should be zero because it is energy dissipated by the motor.
• Initial Rotor Speed: This is a starting speed of the motor that at what speed the motor will start.

Temperature Dependency

• Resistance temperature coefficient:93e-3 1/K
• Measurement temperature: 25 deg C

Thermal Port

• Thermal mass: 20000 J/K
• Initial temperature: 25 deg C

Thermal Port is connected with Temperature sensor Block to measure the motor temperature. Also, Ideal Rotational Motion Sensor is used to measure the motor speed.

H-BRIDGE & MOTOR CONTROLLER

The H-Bridge block represents an H-bridge motor driver.

Simulation mode and Load Assumption Settings

• Power Supply: The power supply is default mode i.e. Internal.
• Simulation Mode: Here I selected Averaged mode and this mode has two Load current characteristics options:

 Smoothed

Unsmoothed or discontinuous

• Regenerative Braking: Always enabled (suitable for linearization), this option can be used when the controller always sets the REV flag to ensure regenerative braking.
• Load Current Characteristics: Smoothed, it’s a default option and it assumes that the current is practically continuous due to load inductance.

Input Thresholds

• Enable threshold voltage: 1.5 V, this is the above value of PWM at which H-Bridge start.
• PWM signal amplitude: 5.0 V, this is the amplitude of the signal at the PWM input. Here I used it as the default mode.
• Reverse threshold voltage: 1.5 V, here I changed this value.
• Braking threshold voltage: 2.5 V

Bridge Parameters

• Output voltage amplitude: 60.8 V, this parameter will be active only when we select Internal for Power Supply mode and it’s an amplitude of the voltage across the H-Bridge.
• Total bridge on resistance: 0.1 ohms,
• The freewheeling diode on resistance: 0.05 ohm
• Measurement Temperature: 25 degC

Temperature Dependency

• Total bridge on resistance at second measurement temperature:00001 ohm
• Freewheeling diode on resistance at second measurement temperature: 001 ohm
• Second measurement temperature:15 degC

Thermal Port

• Thermal mass: 20000 J/k
• Initial temperature: 25 degC

Detail about connection

• PWM: Pulse-width modulated signal.
• REF: Reference, it is an electrical conversing port associated with the floating zero volts.
• REV: Reverse, it is an electrical conserving port associated with the voltage that controls when to reverse the polarity of the H-Bridge block output.
• BRK: BRK, it is an electrical conserving port associated with the voltage that controls when to short circuit the H-Bridge block output.

Here PWM output port is connected with PWM input port of controlled PWM voltage. The REF and REV port are connected with REF port of controlled PWM voltage port. The BRK port is connected with a controlled voltage source.

The positive (+) terminal is connected with the positive (+) port of current sensor and negative (-) port is connected with the negative (-) port of DC motor.

Thermal port (H) is connected with temperature sensor to measure the temperature of controller.

CONTROLLED PWM VOLTAGE

The Controlled PWM Voltage block represents a pulse-width modulated (PWM) voltage source. The input detail is as given below.

Detail about the connection

• ref+ — Positive terminal, this port is a positive electrical reference and connected with controlled voltage source positive terminal.
• ref- — Negative terminal, this port is a negative electrical reference and connected with the negative terminal of the controlled voltage source.
• PWM — Pulse-width modulated signal, this port is electrical reference port and connected with PWM port of H-Bridge.
• REF — Floating zero-volt reference, this port is connected with REF and REV of H-Bridge port.

PWM Setting

• PWM frequency: 1000 Hz
• Sample time: 1e-6 s
• Input voltage for 100% duty cycle: 2 V
• Output voltage amplitude: 60.8 V

CONTROLLED VOLTAGE SOURCE

The Controlled Voltage Source block represents an ideal voltage source that is powerful enough to maintain the specified voltage at its output regardless of the current flowing through the source.

The block has one physical signal input port and two electrical conserving ports associated with its electrical terminals.

SOLVER CONFIGURATION

Solver configuration is used to begin the simulation and it is needed to solve the Simulink model. Here it is connected with controlled PWM voltage and H-Bridge negative connection by combination with electrical reference i.e ground signal.

LONGITUDINAL DRIVER & PID

The Longitudinal Driver block implements a longitudinal speed-tracking controller

The detail of inputs is as given

Detail about parameter

• Control Type: PI it is a Proportional-integral (PI) control with tracking windup and feed-forward gains.

• Reference and feedback unit: m/s

Detail about connection:

• VelRef: Reference vehicle velocity is connected with speed result block. Its unit is m/s.
• VelFdbk — Longitudinal vehicle velocity is connected with integrator block for continuous-time integration of VelFdbk signal.
• Grade — Road grade angle is connected with constant block so that we can use our specific value, here the value is 0 which I used.
• Info — Bus signal, Here I used this signal to terminate the signal block, basically it’s an output port.
• AccelCmd — Commanded vehicle acceleration is connected with SUM block input signal by combination with PID.

• DecelCmd — Commanded vehicle deceleration is connected with SUM block input signal by combination with PID.
• The output PID saturation is connected with controlled voltage source.

PID

This block implements continuous- and discrete-time PID control algorithms and includes advanced features such as anti-windup, external reset, and signal tracking. You can tune the PID gains automatically using the 'Tune...' button (requires Simulink Control Design).

DISTANCE CALCULATION

• Here the main block is an integrator, Divide, time block and for the result we have to use display block that will display the distance.
• Detail about connection:
• Integrator
• The output port of the vehicle body is connected with the integrator block.
• Divide
• The output of the integrator block is connected with divide where it will be divided by time to get the final output.
• Time
• The output of time block is connected with the divide block. Here time is taken as 3600 s.

RESULTS

Depending upon three drive cycle we will get following results.

For UDDS drive cycle (Urban Dynamometer Driving Schedule) a vehicle run for 1369 sec and the total distance covered during this is 12.7404 km and at that time the energy consumption was 248.6 kW, Temperature rises in motor 302.2 degC and temperature rise in controller 303.1 degC.

Output Results based on ideal condition and PID Tunned. If we tunned the model then we will get following result as I have compared in table.

Plotted results: Ideal Condition Vs PID Tunned

Energy Consumption

Motor Temperature

Controller Temperature

Vehicle Speed

SOC

Distance

For HWFET drive cycle (Highway Fuel Economy Driving Schedule) a vehicle run for 765 sec and the total distance covered during this is 16.8552 km and at that time the energy consumption was 248 kW, Temperature rises in motor 300.4 degC and temperature rise in controller 301 degC.

Output Results based on ideal condition and PID Tunned. If we Tunned the model then we will get following result as I have compared in table.

Plotted results: Ideal Condition Vs PID Tunned

Energy Consumption

 

Motor Temperature

 

Controller Temperature

 

Vehicle Speed

 

SOC

 

Distance

For FTP75 drive cycle a vehicle run for 2474 sec and the total distance covered during this is 18.2808 km and at that time the energy consumption was 455 kW, Temperature rises in motor 304.5 degC and temperature rise in controller 305.9 degC.

Output Results based on ideal condition and PID Tunned. If we Tunned the model then we will get following result as I have compared in table.

Plotted results: Ideal Condition Vs PID Tunned

Energy Consumption

 

Motor Temperature

 

Controller Temperature

 

Vehicle Speed

 

SOC

 

Distance

 

Conclusion

• If we compare with real model then the motor, battery and controller temperature is controlled by using air cooling system because it is not high.
• The MATLAB model of e-rickshaw is created by using Li-ion Battery 60.8 V 160Ah and PM Brushed DC Motor.
• Also, after PID tunning the temperature is rises and we get better distance as compared with non-tunned electric rickshaw.