Project-1: Modelling an electric Car with Li-ion battery

AIM OF THE PROJECT: Modelling an Electric Car with Li-Ion Battery using various Driving Source as a Speed Reference

OBJECTIVES:

• To create a Simple Matlab Model of an Electric Car showing all its major components as a subsystem starting from the Motor to the Vehicle Dynamics.

• To analyse and estimate the SOC, Vehicle Velocity, Distance Covered by the vehicle and overall energy consumption at different driving source reference.

• Analysis of all the above parameters is done w.rto Four Driving Cycles given as FTP-75, WOT and Constant Speed of 45kmph for 100km.

• To simulate the entire model by changing the parameters corresponding to various subsystem like. DC Motor, H-Bridge, Vehicle Body, so as to identify the dependencies of the subsystem parameters over the entire MATLAB model.

• To reduce the deviation of the actual vehicle velocity w.r.to the reference velocity which identifies as a error to the system and minimize the error to some extent by introducing a Pl Controller Subsystem.

INTRODUCTION:

An electric vehicle (EV) is one that operates on an electric motor, instead of an internal-combustion engine that generates power by burning a mix of fuel and gases. Therefore, such as vehicle is seen as a possible replacement for current-generation automobile, in order to address the issue of rising pollution, global warming, depleting natural resources, etc. Though the concept of electric vehicles has been around for a long time, it has drawn a considerable amount of interest in the past decade amid a rising carbon footprint and other environmental impacts of fuel-based vehicles.

Benefits of Electric vehicle:

• They produce no tailpipe emissions, so are better for the planet.

• better utilise the electricity network

• help EV owners avoid higher-cost charging periods

• help EV owners avoid higher-cost charging periods

• help support the integration of more small and large-scale renewable energy systems into the electricity grid

• The cost of the electricity required to charge an EV is around 40% less than the cost to use petrol for a similar sized vehicle driving the same distance. The cost will be lower if you charge your EV from your solar PV system or at free charging stations.

• An Electric Vehicle (EV) has fewer moving parts than a conventional petrol/diesel car. Servicing is relatively easy less frequent and overall cheaper than a petrol/diesel vehicle. All EV batteries degrade (become less efficient). Most car manufacturers warrant EV batteries to not degrade below a certain level for around eight years. It may become necessary to replace a battery in an EV in the time you own it.

In India, the first concrete decision to incentivise electric vehicles was taken in 2010. According to a Rs 95 crore scheme approved by the Ministry of New and Renewable Energy (MNRE), the government announced a financial incentive for manufacturers for electric vehicles sold in India. The scheme, effective from November 2010, envisaged incentives of up to 20 per cent on ex-factory prices of vehicles, subject to a maximum limit. However, the subsidy scheme was later withdrawn by the MNRE in March 2012.

In 2013, India unveiled the National Electric Mobility Mission Plan (NEMMP) 2020' to make a major shift to electric vehicles and to address the issues of national energy security, vehicular pollution and growth of domestic manufacturing capabilities. Though the scheme was to offer subsidies and create supporting infrastructure for e-vehicles, the plan mostly remained on papers. While presenting the Union Budget for 2015-16 in Parliament, then finance minister Arun Jaitley announced faster adoption and manufacturing of electric vehicles (FAME), with an initial outlay of Rs 75 crore. The scheme was announced with an aim to offer incentives for clean-fuel technology cars to boost their sales to up to 7 million vehicles by 2020.

Another way EVS are different is that range and efficiency aren't directly related. That's because of charging losses, roughly 85 to 90 percent of the total energy that comes from the wall makes it into the battery pack. That's why ther are two terms used: efficiency, which can be expressed in MPGe, includes charging losses, while consumption, the energy use while driving, doesn't include them.

The EV range test is done at a steady 75 mph, because highway driving is where range matters most. If ones looking to cover 500 or 1000 miles in a day, it necessarily has to be done at high speeds. There's just not enough hours in the day to do otherwise. Even the shortest-range EV can manage more than 7 hours of slogging through city traffic at a average speed of, say, 15 mph. Also, unlike a gas-powered vehicle, an EV's consumption increases dramatically as speeds rise. Of course, as with all cars, aerodynamic drag inflates with the square of speed, but EVS are particularly affected as all but the Porsche Taycan lack multiple gears. So, a higher vehicle speed means the electric motor is spinning at a faster and less-efficient point.

Model representation of the electric car in MATLAB-SIMULINK:

Drive cycle source subsystem:
The drive cycle subsystem consists of the following blocks which are as follows:

Here there are 3 types of velocity reference given to the system, out of which two are the default driving source implemented from the 'Drive Cycle Source' Block whereas the the third one is a custom Drive Cycle of excel repectively.

i) Drive Cycle Source Block:

• This block generates a standard or user-specified longitudinal drive cycle. The block output is the specified vehicle longitudinal speed, and the functions are given as follows:

• Predict the engine torque and fuel consumption that a vehicle requires to achieve desired speed and acceleration for a given gear shift reference.

• Produce realistic velocity and shift references for closed loop acceleration and braking commands for vehicle control and plant models.

• Study, tune, and optimize vehicle control, system performance, and system robustness over multiple drive cycles.

This block is used to determine which of several inputs to the block passes to the output. The block bases this decision on the value of the first input. The first input is the control input and the remaining inputs are the data inputs. The value of the control input determines which data input passes to the output.

In this porject as there are 4 types of velocity reference used so that's why 4 data ports are required as shown below.

Proportional-Integral-Derivative (PID) control is the most common control algorithm used in industry and has been universally accepted in industrial control. The popularity of PID controllers can be attributed partly to their robust performance in a wide range of operating conditions and partly to their functional simplicity, which allows engineers to operate them in a simple, straightforward manner. The basic idea behind a PID controller is to read a sensor, then compute the desired actuator output by calculating proportional, integral, and derivative responses and summing those three components to compute the output.

The three major response of the PID Controller are discussed below:

Proportional Response: The proportional component depends only on the difference between the set point and the process variable. This difference is referred to as the Error term. The proportional gain (Kc) determines the ratio of output response to the error signal. For instance, if the error term has a magnitude of 10, a proportional gain of 5 would produce a proportional response of 50. In general, increasing the proportional gain will increase the speed of the control system response. However, if the proportional gain is too large, the process variable will begin to oscillate. If Ke is increased further, the oscillations will become larger and the system will become unstable and may even oscillate out of control.

• Integral Response: The integral component sums the error term over time. The result is that even a small error term will cause the integral component to increase slowly. The integral response will continually increase over time unless the error is zero, so the effect is to drive the Steady-State error to zero. Steady-State error is the final difference between the process variable and set point. A phenomenon called integral windup results when integral action saturates a controller without the controller driving the error signal toward zero.

• Derivative Response: The derivative component causes the output to decrease if the process variable is increasing rapidly. The derivative response is proportional to the rate of change of the process variable. Increasing the derivative time (Ta) parameter will cause the control system to react more strongly to changes in the error term and will increase the speed of the overall control system response. Most practical control systems use very small derivative time (Ta), because the Derivative Response is highly sensitive to noise in the process variable signal. If the sensor feedback signal is noisy or if the control loop rate is too slow, the derivative response can make the control system unstable.

The Corresponding MATLAB Model of the PID Controller is shown below:

The MATLAB PID Controller block performs the same function described above; the values of the PID gain is implemented after linearizing the plant with a step response output and correspondingly track the error input to the PID block, the valus of the PID gains are hown below:

i) Saturation Block:

The Saturation block produces an output signal that is the value of the input signal bounded to the upper and lower saturation values. The upper and lower limits are specified by the parameters Upper Limit and Lower Limit in the Command Block.

This block is responsible for the creation of the Pulse Width Modulated (PWM) signal across the PWM and REF ports. The output voltage is zero when the pulse is low, and is equal to the Output voltage amplitude parameter when high. At time zero, the pulse is initialized as high unless the duty cycle is set to zero or the Pulse delay time is greater than zero.

For the Electrical Input ports variant of the block, the demanded duty cycle is:

100*Vref-Vmin /V-Vmin percent

where:

Vref is the reference voltage across the ref+ and ref- ports.

Vmin is the minimum reference voltage.

Vmax is the maximum reference voltage.

In this project, the Simulation Mode is choosen as Averaged where the ouput signal will be constant with value equal to the averaged PWM signal. The PWM frequency is choosen as 6kHz with an output voltage amplitude of 300V respectively, as shown in the below figure:

Motor and its controller subsystem:

Controlled PWM voltage:

H Bridge is a simple electronic circuit which enables us to apply voltage to load in either direction. It is commonly used in robotics application to control DC Motors. By using H Bridge we can run DC Motor in clockwise or anticlockwise directions. This circuit is also used to produce alternating waveforms in inverters.

In MATLAB, the H-Bridge block performs the same function highlighted above which is ultimately driven by the Contolled PWM Voltage Block in Averaged Mode as per the project requirement. 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.

For Averaged Simulation Mode, the load current characteristics is set to Smoothed rather than Discontinuous. As per the requirement, the thermal port of the H-Bridge is also enabled so as to monitor the temperature variation of the converter w.r.to the vehicle velocity output.

This block constitute the the electrical and torque characteristics of a DC motor. The assumption of this block is that there is 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 no-load speed and stall torque. When a positive current flows 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 type of Motor choosen is the Permanent Magnet Type so that it resemblance the BLDC type of Motor which is most commonly used in the Electric Vehicle. In this project, the Thermal Port of the DC Motor block is used to simulate the effects of copper resistance losses that convert electrical power to heat.

Here the 'C' port represents the casing of the Motor which needs to be grounded using the Mechanical Rotational Reference Frame whereas the 'R' port consitutes the Rotor of the Motor which is connected to the Gear system of the vehicle dynamics. The value of the parameters considered for DC Motor block is shown in figure below:

iv) Controlled Voltage Source:

The block represents an ideal voltage source that is powerful enough to maintain the specified voltage at its output regardless of the current passing through it. The output voltage is V = Vs, where Vs is the numerical value presented at the physical signal port.

Two quantities of the volatage source block is required; one one is required for to drive the Controlled PWM Volatge source and another is required to drive the Braking command of the H-Bridge. The respective volatge of this block is controlled as per the acceleration command(to control the PWM voltage source) and the De-acceleration command(to control the Braking voltage of the H-Bridge) of the Longitudinal Driver.

v) Current Sensor:

The block represents an ideal current sensor, that is, a device that converts current measured in any electrical branch into a physical signal proportional to the current. Connections + ve and ve are conserving electrical ports through which the sensor is inserted into the circuit. Connection T is a physical signal port that outputs current value.

The positive and the negative part of the block is connected betwee the H-Bridge and the DC Motor whereas the physical port 'I' is connected to the Controlled Current Source of the Battery Management system of the E-Rickhaw Model.

vi) Temperature Sensor:

This block measures temperature in a thermal network. There is no heat flow through the sensor. The physical signal port T reports the temperature difference across the sensor. The measurement is positive when the temperature at port A is greater than the temperature at port B.

Here ther are two temperature sensors used; one is for the measurement of the temperature in the H-Bridge while the other for the DC-Motor. The output of the Sensor is taken from the physical port 'T' which is connected to the Scope in order to analyse the temperature profile of both the Motor and its Converter Block.

4. Vehicle Dynamic Subsystem:

The goals of vehicle dynamics are twofold: First, they make vehicles safer by intervening to provide support in problematic driving situations. Second, vehicle dynamics control systems can be adjusted to implement the individual DNA of an OEM. Because vehicle dynamics control systems influence vehicle movement, several of the systems have an important role to play in achieving the goal of autonomous driving. For example, the ESC deploys the braking action in autonomous vehicles. Vehicle dynamics are undergoing continuous development to further improve vehicle safety and comfort. As a result, ESC now encompasses a variety of additional support functions, significantly increasing the effort needed for validation during development.

This subsystem consists of blocks which are configured as follows:

This block represents a two-axle vehicle body in longitudinal motion. The block accounts for body mass, aerodynamic drag, road incline, and weight distribution between axles due to acceleration and road profile. This block gives the option of having the same or a different number of wheels on each axle with Optional inclusion of pitch and suspension dynamics or additional variable mass and inertia. The vehicle body block does not move vertically relative to the ground.

This block consists of an all total of 6 connection port; out of which 'H' is the Mechanical Translational Conserving port associated with the horizontal motion of the vehicle body and its connected to the 'H' port of the wheel hub of the tire through which the resulting traction motion of the tires will get generated. 'V' is the physical output port which is used to examine and monitor the vehicle velocity curve, 'NF' and 'NR' are also physical output ports but they represent fron and rear normal wheel forces and due to this reason they are connected to the 'N' of the tires through the forces will get act on the wheel for rotation, 'W' and 'beta' are physical signal input ports corresponding to headwind speed and road inclination angle.

The value of the parameters given to the vehicle body is shown below:

The Tire (Magic Formula) block models a tire with longitudinal behavior given by the Magic Formula [1], an empirical equation based on four fitting coefficients. The block can model tire dynamics under constant or variable pavement conditions. The longitudinal direction of the tire is the same as its direction of motion as it rolls on pavement and to increase the fidelity of the tire model, the properties can be specified such as tire compliance, inertia, and rolling resistance. However, these properties increase the complexity of the tire model and can slow down simulation. Consider ignoring tire compliance and inertia if simulating the model in real time or if preparing the model for hardware-in-the-loop (HIL) simulation.

Same as vehicle body, this block aslo consists of 4 connection port; out of which 'A' is the mechanical rotational conserving port for the wheel axle and it is connected to the Gear arrangement of the vehicle. 'H' is the mechanical translational conserving port for the wheel hub through which the thrust is developed by the tires of the vehicle and it is connected to the 'H' port of the vehicle body for initiation of the horizontal motion. 'N' is the physical signal input port that applies the normal force acting on the tire and it is connected to the 'NR' and 'NF of the vehicle body.

The values of the parameters assigned to the tires are shown below:

iii) Simple Gear:

This block represents a fixed-ratio gear or gear box. No inertia or compliance is modeled in this block. You can optionally include gear meshing and viscous bearing losses.

Connections B (base) and F (follower) are mechanical rotational conserving ports which are connected to the Shaft Input of the DC Motor and the 'A' port of the wheel and axle respectively. The relation between base and follower rotation directions with the Output shaft rotates parameter.

iv) Inertia:

The block represents an ideal mechanical rotational inertia. The block positive direction is from its port to the reference point which means that the inertia torque is positive if the inertia is accelerated in the positive direction.

The value of the Inertia is choosen to be 4kg*m2.

5. Battery Management Subsystem:

The BMS will also control the recharging of the battery by redirecting the recovered energy (i.e.- from Regenerative Braking) back into the battery pack (typically composed of a number of battery modules, each composed of a number of cells). Battery thermal management systems can be either passive or active, and the cooling medium can either be air, liquid, or some form of phase change. Air cooling is advantageous in its simplicity. Such systems can be passive, relying only on the convection of the surrounding air, or active, utilizing fans for airflow. Commercially, the Honda Insight and Toyota Prius both utilize active air cooling of their battery systems.

The major disadvantage of air cooling is its inefficiency. Large amounts of power must be used to operate the cooling mechanism, far more than active liquid cooling. The additional components of the cooling mechanism also add weight to the BMS, reducing the efficiency of batteries used for transportation. Liquid cooling has a higher natural cooling potential than air cooling as liquid coolants tend to have higher thermal conductivities than air. The batteries can either be directly submerged in the coolant or coolant can flow through the BMS without directly contacting the battery. Indirect cooling has the potential to create large thermal gradients across the BMS due to the increased length of the cooling channels. This can be reduced by pumping the coolant faster through the system, creating a tradeoff between pumping speed and thermal consistency.

The configuration of the Subsystem is shown below:

This block implements a generic dynamic model that represents most popular types of rechargeable batteries with the following assumptions:

• The internal resistance is assumed to be constant during the charge and discharge cycles and does not vary with the amplitude of the current.

• The parameters of the model are derived from the discharge characteristics. The discharging and charging characteristics are assumed to be the same.

• The capacity of the battery does not change with the amplitude of the current (there is no Peukert effect).

• The self-discharge of the battery is not represented. It can be represented by adding a large resistance in parallel with the battery terminals.

The equivalent circuit of the Battery Block is shown below:

When the battery gets charge then there is a exponential voltage drop, and the width of the drop is depends upon the Battery Type. Since the battery is rechargable so a considerable amount of charge can be extracted from the battery until the voltage drops below the battery nominal voltage.

As per the project requirement, the Nominal Voltage of the Battery is set as 300V with initial SOC of 100%.

The positive terminal of the battery is connected to the Controlled Current Source Block where the current is controlled as per the voltage of the DC-motor.

The value of the parameters set for the Battery is given as a figure below:

ii) Controlled Current Source:

This block is responsible converting the Simulink input signal into an equivalent current source. The generated current is driven by the input signal of the block. The block is initialized as a AC current source type and the simulation is started in the steady state condition, so therefore the block input must be connected to a signal starting as a sinusoidal or DC waveform corresponding to the initial values.

The positive and the negative terminals of the block is connected across the Battery and the physical port 'S' is connected to the physical output port 'l' of the Current Sensor of the DC Motor Subsystem. It is arranged in a fashion that the current drawn by the DC Motor is coming form the Generic Battery.