Welcome to the South Asian Development of Vehicle Model in Matlab simulation, in this situation, we
will develop the mathematical model of vehicle by solving the differential equation with the help of
Matlab simulation.
If you are already about the using of Matlab simulation for solving the differential equation, then
it's fine.
Otherwise we will also go step by step procedure for this particular example of vehicle model we have
already discussed about the dynamic equation of the vehicle and in decision value the simulation for
developing the Mathematica model.
We will use this equation they applied for is equal to A that is M into my DETI with the velocity plus
opposing force of aerodynamic drag.
So this opposing force and plus if it is a vehicle, is at incline angle B to then the component of
gravitational force is Modisane Beita to these three force and opposing the supply force.
And it will result in equilibrium speed for applying for.
So it will determine the stability, steady state speed and also give us the idea about the response,
how fast or slow we will let you the steady state speed for the Applied Force.
So this is the system level simulation here.
Our main input parameters that weight and inertia of the vehicle and supply force.
So this is called the system simulation because we use the general assistance simulation to represent
the mechanical, electrical or even magnetic or chemical system.
Next, higher in the simulation level at the unit level simulation that we used up in that simulation
of different units like the motor converter than engine or attacks and different segments, level simulation.
And then we join this simulation together.
This is next step.
We are not going to discuss that a unit level and furthermore, for the higher prediction and to predict
the more information we use, the component level simulation simulation of Las Vegas, simulation of
joint, and then we can work together.
So because this is the multidisciplinary course, we use the first system level simulation here we are
designing the simulation of vehicle simulation models vehicle.
So this differential equation will be simulated in Matlab if we use this equation.
So but it is equal to supply force.
Applied Force minus 40 is that dynamic drag force and minus Modisane Beta.
This can be easily simulated with the help of Simulant Library of.
Let's see.
Here is the model I developed for the vehicle so we can see the, the.
And platforms and component design.
So if you recall this equation at this point, so we are having the question and to be reminded is equal
to supply force F that is force.
We apply opposing force represented by minus sign F. Lee and M.G. S. Bita.
So opposing force that F3 and M.G. to.
So we had m divided is equal to F minus F and minus Modisane Bita.
So we'll see what this FBN, what it means and B.
But at this point what we need to realize, the equation that we discussed is realized at this point
m divided is equal to F minus 70 minus Modisane.
Now in itself a question of the sometimes we use the negative side to represent it is opposite to the
direction of velocity.
But to understand by assuming the direction of velocity in the positive direction, it will oppose SOYER
negative SANWAL.
So after this point, if we move forward, then if we want to integrate it and before if we want to
divide by the mass with the gain block, you can find the gain block and commonly used block yet again
you can it.
And this gain block, you can set whatever you want.
So for more clarity, I read the same quote.
One by 200, 200 is the math.
So here we have assumed the vehicle math is 200 cagy.
And if we divide this M divided by 200.
So what will remain at the site?
So we will be by DETI.
So here we are having DBI did not feel the integration of divisibility then integration block will be
used that also you can find.
Yes.
And disintegrator block we can use.
So integrator is used so that at the end of integrated output will be regex.
So integration up divided this way.
So what we want, we want to predict if we apply a certain amount of force, what will be the speed.
Yet force is also constant, steady state, but in actual spirit it will be in actual performance.
It will be ready.
We'll see later how we can do this.
But this is the vehicle simulation.
We can do this for the applied for what we've done speed yet spellbind meters per second.
And if you remember the equation of the aerodynamic force, then we are having this out in component
Pantelleria, concentric Koshien, much density of air and this is for one by two multiplied by zero
point one by two, the frontal area, a direct quotient and mass density of at rule.
Yet we use the typical values one point two zero point four and one point two.
This is representing one by two entities representing the Met function that is squared squared off the
velocity.
So whatever input it will be had and it will output.
So yeah, we need to the squared output because we also need to.
Use the sign off velocity so that if velocity is reversed, the direction of force, FDR would also
reverse, but because here we are not going to reverse the direction we're applying the negative force.
So for the moment, we can let it only to function as a square.
You can find the math function from the SIMULANT library and met operator.
You can find this math function.
And if you open this parameter, you can select the function you want and magnitude square that can
use the input magnitude will be scared and the square will be the output at this terminal.
So you can see this equation of Apne V squared multiplied by one by two, multiplied by one point two
multiplied by zero point for the and multiply by frontal area one point two that this is representing
the FBI aerodynamic drag force that is opposing to the Applied Force.
Now, come to this spot, this is and this would be to say a few.
Go and read the William M Jerrell Agenda Masses 200 Kaiji into nine point eight one is the constant
so and Rita is currently we can see it from here.
Currently it is set to zero and sine function we can use from the Met operator.
This same function can be used from Meritocrat, so this will become wita into to sign to sign Bitta
and sign it and multiply by M.G..
So this will be this input becomes M.G. sign Bita.
So this is our complete simulation model of the vehicle having the weight mass.
And if we are having the radius, then we can also supplied the talk instead of force.
That Burnsy not to simulate this model, we need to just run it for the particular model.
Second, by default, it will be 10 seconds in your model.
You need to include the second because of the high inertia.
It will take too much time in physical seconds so our vehicle cannot reach to speed at 13 kilometers
per hour in the fraction of second in one second or two seconds.
So we need to simulate for certain amount of time support and setting the two under second and fourth
applied force in Newton and Newton.
If I simulate, we will see this, this represents the speed and meter per second and final speed,
let's say, is it?
The statistics are not to check this.
We need to check the performance so you can see it is not showing the exponential plot.
And this is still increasing.
It is not steady state speed.
We need to increase the second.
So we will do the two things for refining this data point.
We need to we know that this is exponential response.
But for the defense, you can go to the simulation model configuration parameter and under the data
input expert.
You can see the zero option under the safe option output option if, in fact, you need to increase
the defense factor if output is not.
So when you are using the same Willink model component, not the discrete and not using any electrical
sympathectomy library component of the simulation will be very fast.
But you need to use this different factor.
You can increase to 10, 20 or I used 50 for refinement.
Even if you design functional sine wave, sometime you will find the distortion.
We often think that this refined factor and let's run it again.
So we see this is now our actual response, exponential response of differential equation.
And we can see the steady state speed is eighteen point six three meters per second.
So this is what our we model will give us the exact idea.
If we apply the constant photon at this rate, speed will increase and what the final steady state of
the vehicle for the particular amount of force and.
We will have also at how much time, what will be just be retained by the weekend, we can convert it
in cell phone from the meters per second to kilometer.
But with this game clock, so if you have the speed in kilometer per hour, we will have around sixty
five.
You can see.
Sixty seven kilometer per hour, final speed, maximum speed, steady state speed, and this development,
we can say, will also make considering the Guarascio one, what we can see the girls drive six three
eight eight PM.
You can see the evolution, but Mynott.
So to convert the minute into second, it is multiplied by 60 because of the evolution minute.
So it will become the evolution.
But second and one, the evolution representa to buy at meters to represent one.
The evolution is divided by two by two into three point one, four into Arietta areas that we assume.
So it is around zero five to seven, nine is around 11 each.
We can see it is we are doing the mopper or such kind of vehicle because we are a motorcycle as the
radius around soundin each.
So we are not.
So if you are using the model bike, then accordingly you can set the radius for real speed and you
can use it.
So we will also have the distance covered because this is the velocity of the military, so if you want
to know how much distance travel at the end of this time, we can also see distance travel is around
three thousand in between 3000 to 30000 meter administrator, three point five km.
In 200 second.
So this is all output, we will help for this input, and this is called a system level model of the
vehicle.
Now we can also talk component instead of force if we want.
So what we need to do, we need to use the gain.
So what is the talk I read again?
So it will remain force if it is dark, a new transmitter.
So I am changing this to talk about and become.
Back and force is equal to talk radio so we can talk is equal to force, multiplied by radius.
So if I use this is one by a radius is zero point two seven nine.
But this is talk, this is for now, if we apply the ten hundred Newton Newton of talk, then we can
see the performance speed is 120 greater than 120.
Steady state speed is 120 seven km.
But this is inevitable.
Second will be so you can use the display block for all this also so you can measure the speed and relative
and distance travel for the airplane.
So this is how we can also include the angle to observe the performance.
So this is how we can simulate the vehicle model with the help of Matlab blocks.
Now, what we need to do is you need to store the characteristics by doing the experiment in this simulation
model so that you need to do is starting from the minimum task that is, say, five Newton Mitka dissimulate
eight and record the steady state speed intermap kilometer, but not ensure that it is steady state
speed, because when you reduce to talk, it will take more time to read the steady state speed they
produce.
Taking longer than your simulation time, then it may not be steady state speed.
So yet I need to return.
It is kilometer per.
Ah.
And this is.
And we.
So let's observe it is state or not, you can say this is not a steady state speed.
When we are playing the less amount of risk, it will take more time to fly under so we can have steady
state speed.
So you can see now the steady state speed.
So it is fine.
So what we want.
We want to.
The talk and measure the speed in KM.
But I will use this table.
You can meet the.
So for the five, the spirit is twenty eight point four.
Let's do the experiment one more time, increased by five to four.
The ten Newton meters statistics is forty
four point forty point one six.
Likewise, you need to plug up to the hundred with the increment of five.
So.
For the 15 days, forty nine point one, so when you plot these characteristics, toxified character,
it called the toxified characteristic of a vehicle, we're measuring the statistics.
We will use this characteristic for merging the different system level simulation, electrical with
this mechanical model of the vehicle.
So this talk is generated.
So, you know, this experiment and Shari'ah result of the task with characteristic of the vehicle in
terms of local people as well as in terms of plot.
So it will be exponentially increasing.
You will realize that it will increase exponentially.
But this is called the speed characteristic of our speed makeup that can be predicted by this model.
So this is the output in terms of speed.
And acceleration performance also we can predict and distance travel, but main important thing, we
are interested in the actual speed and the acceleration of the vehicle and this talk is generated from
the electric motor.
So in that section of the electric drive, we will discuss about the aspect of electrical, motor and
system level simulation of electric motor that can generate this talk and this talk.
When applied to the vehicle.
We can predict the performance of the system of combining the electrical as well as the mechanical systems.
When we supply the voltage to the electrical system, it will generate the thought that we will see
the motor and this is applied to the vehicle model and it will result in speed.
So when we supply the voltage, we will get the speed and the performance that.
Hope you got that basic idea about the system level simulation of vehicle with the help of Matlab simulation
model.