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Welcome to the South Asian Development of Vehicle Model in Matlab simulation, in this situation, we



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will develop the mathematical model of vehicle by solving the differential equation with the help of



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Matlab simulation.



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If you are already about the using of Matlab simulation for solving the differential equation, then



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it's fine.



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Otherwise we will also go step by step procedure for this particular example of vehicle model we have



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already discussed about the dynamic equation of the vehicle and in decision value the simulation for



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developing the Mathematica model.



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We will use this equation they applied for is equal to A that is M into my DETI with the velocity plus



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opposing force of aerodynamic drag.



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So this opposing force and plus if it is a vehicle, is at incline angle B to then the component of



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gravitational force is Modisane Beita to these three force and opposing the supply force.



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And it will result in equilibrium speed for applying for.



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So it will determine the stability, steady state speed and also give us the idea about the response,



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how fast or slow we will let you the steady state speed for the Applied Force.



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So this is the system level simulation here.



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Our main input parameters that weight and inertia of the vehicle and supply force.



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So this is called the system simulation because we use the general assistance simulation to represent



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the mechanical, electrical or even magnetic or chemical system.



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Next, higher in the simulation level at the unit level simulation that we used up in that simulation



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of different units like the motor converter than engine or attacks and different segments, level simulation.



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And then we join this simulation together.



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This is next step.



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We are not going to discuss that a unit level and furthermore, for the higher prediction and to predict



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the more information we use, the component level simulation simulation of Las Vegas, simulation of



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joint, and then we can work together.



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So because this is the multidisciplinary course, we use the first system level simulation here we are



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designing the simulation of vehicle simulation models vehicle.



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So this differential equation will be simulated in Matlab if we use this equation.



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So but it is equal to supply force.



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Applied Force minus 40 is that dynamic drag force and minus Modisane Beta.



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This can be easily simulated with the help of Simulant Library of.



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Let's see.



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Here is the model I developed for the vehicle so we can see the, the.



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And platforms and component design.



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So if you recall this equation at this point, so we are having the question and to be reminded is equal



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to supply force F that is force.



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We apply opposing force represented by minus sign F. Lee and M.G. S. Bita.



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So opposing force that F3 and M.G. to.



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So we had m divided is equal to F minus F and minus Modisane Bita.



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So we'll see what this FBN, what it means and B.



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But at this point what we need to realize, the equation that we discussed is realized at this point



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m divided is equal to F minus 70 minus Modisane.



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Now in itself a question of the sometimes we use the negative side to represent it is opposite to the



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direction of velocity.



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But to understand by assuming the direction of velocity in the positive direction, it will oppose SOYER



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negative SANWAL.



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So after this point, if we move forward, then if we want to integrate it and before if we want to



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divide by the mass with the gain block, you can find the gain block and commonly used block yet again



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you can it.



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And this gain block, you can set whatever you want.



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So for more clarity, I read the same quote.



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One by 200, 200 is the math.



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So here we have assumed the vehicle math is 200 cagy.



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And if we divide this M divided by 200.



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So what will remain at the site?



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So we will be by DETI.



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So here we are having DBI did not feel the integration of divisibility then integration block will be



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used that also you can find.



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Yes.



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And disintegrator block we can use.



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So integrator is used so that at the end of integrated output will be regex.



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So integration up divided this way.



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So what we want, we want to predict if we apply a certain amount of force, what will be the speed.



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Yet force is also constant, steady state, but in actual spirit it will be in actual performance.



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It will be ready.



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We'll see later how we can do this.



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But this is the vehicle simulation.



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We can do this for the applied for what we've done speed yet spellbind meters per second.



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And if you remember the equation of the aerodynamic force, then we are having this out in component



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Pantelleria, concentric Koshien, much density of air and this is for one by two multiplied by zero



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point one by two, the frontal area, a direct quotient and mass density of at rule.



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Yet we use the typical values one point two zero point four and one point two.



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This is representing one by two entities representing the Met function that is squared squared off the



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velocity.



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So whatever input it will be had and it will output.



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So yeah, we need to the squared output because we also need to.



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Use the sign off velocity so that if velocity is reversed, the direction of force, FDR would also



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reverse, but because here we are not going to reverse the direction we're applying the negative force.



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So for the moment, we can let it only to function as a square.



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You can find the math function from the SIMULANT library and met operator.



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You can find this math function.



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And if you open this parameter, you can select the function you want and magnitude square that can



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use the input magnitude will be scared and the square will be the output at this terminal.



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So you can see this equation of Apne V squared multiplied by one by two, multiplied by one point two



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multiplied by zero point for the and multiply by frontal area one point two that this is representing



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the FBI aerodynamic drag force that is opposing to the Applied Force.



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Now, come to this spot, this is and this would be to say a few.



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Go and read the William M Jerrell Agenda Masses 200 Kaiji into nine point eight one is the constant



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so and Rita is currently we can see it from here.



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Currently it is set to zero and sine function we can use from the Met operator.



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This same function can be used from Meritocrat, so this will become wita into to sign to sign Bitta



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and sign it and multiply by M.G..



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So this will be this input becomes M.G. sign Bita.



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So this is our complete simulation model of the vehicle having the weight mass.



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And if we are having the radius, then we can also supplied the talk instead of force.



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That Burnsy not to simulate this model, we need to just run it for the particular model.



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Second, by default, it will be 10 seconds in your model.



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You need to include the second because of the high inertia.



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It will take too much time in physical seconds so our vehicle cannot reach to speed at 13 kilometers



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per hour in the fraction of second in one second or two seconds.



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So we need to simulate for certain amount of time support and setting the two under second and fourth



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applied force in Newton and Newton.



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If I simulate, we will see this, this represents the speed and meter per second and final speed,



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let's say, is it?



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The statistics are not to check this.



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We need to check the performance so you can see it is not showing the exponential plot.



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And this is still increasing.



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It is not steady state speed.



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We need to increase the second.



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So we will do the two things for refining this data point.



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We need to we know that this is exponential response.



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But for the defense, you can go to the simulation model configuration parameter and under the data



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input expert.



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You can see the zero option under the safe option output option if, in fact, you need to increase



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the defense factor if output is not.



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So when you are using the same Willink model component, not the discrete and not using any electrical



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sympathectomy library component of the simulation will be very fast.



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But you need to use this different factor.



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You can increase to 10, 20 or I used 50 for refinement.



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Even if you design functional sine wave, sometime you will find the distortion.



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We often think that this refined factor and let's run it again.



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So we see this is now our actual response, exponential response of differential equation.



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And we can see the steady state speed is eighteen point six three meters per second.



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So this is what our we model will give us the exact idea.



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If we apply the constant photon at this rate, speed will increase and what the final steady state of



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the vehicle for the particular amount of force and.



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We will have also at how much time, what will be just be retained by the weekend, we can convert it



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in cell phone from the meters per second to kilometer.



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But with this game clock, so if you have the speed in kilometer per hour, we will have around sixty



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five.



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You can see.



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Sixty seven kilometer per hour, final speed, maximum speed, steady state speed, and this development,



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we can say, will also make considering the Guarascio one, what we can see the girls drive six three



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eight eight PM.



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You can see the evolution, but Mynott.



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So to convert the minute into second, it is multiplied by 60 because of the evolution minute.



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So it will become the evolution.



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But second and one, the evolution representa to buy at meters to represent one.



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The evolution is divided by two by two into three point one, four into Arietta areas that we assume.



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So it is around zero five to seven, nine is around 11 each.



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We can see it is we are doing the mopper or such kind of vehicle because we are a motorcycle as the



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radius around soundin each.



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So we are not.



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So if you are using the model bike, then accordingly you can set the radius for real speed and you



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can use it.



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So we will also have the distance covered because this is the velocity of the military, so if you want



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to know how much distance travel at the end of this time, we can also see distance travel is around



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three thousand in between 3000 to 30000 meter administrator, three point five km.



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In 200 second.



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So this is all output, we will help for this input, and this is called a system level model of the



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vehicle.



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Now we can also talk component instead of force if we want.



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So what we need to do, we need to use the gain.



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So what is the talk I read again?



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So it will remain force if it is dark, a new transmitter.



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So I am changing this to talk about and become.



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Back and force is equal to talk radio so we can talk is equal to force, multiplied by radius.



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So if I use this is one by a radius is zero point two seven nine.



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But this is talk, this is for now, if we apply the ten hundred Newton Newton of talk, then we can



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see the performance speed is 120 greater than 120.



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Steady state speed is 120 seven km.



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But this is inevitable.



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Second will be so you can use the display block for all this also so you can measure the speed and relative



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and distance travel for the airplane.



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So this is how we can also include the angle to observe the performance.



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So this is how we can simulate the vehicle model with the help of Matlab blocks.



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Now, what we need to do is you need to store the characteristics by doing the experiment in this simulation



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model so that you need to do is starting from the minimum task that is, say, five Newton Mitka dissimulate



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eight and record the steady state speed intermap kilometer, but not ensure that it is steady state



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speed, because when you reduce to talk, it will take more time to read the steady state speed they



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produce.



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Taking longer than your simulation time, then it may not be steady state speed.



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So yet I need to return.



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It is kilometer per.



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Ah.



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And this is.



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And we.



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So let's observe it is state or not, you can say this is not a steady state speed.



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When we are playing the less amount of risk, it will take more time to fly under so we can have steady



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state speed.



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So you can see now the steady state speed.



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So it is fine.



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So what we want.



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We want to.



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The talk and measure the speed in KM.



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But I will use this table.



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You can meet the.



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So for the five, the spirit is twenty eight point four.



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Let's do the experiment one more time, increased by five to four.



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The ten Newton meters statistics is forty



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four point forty point one six.



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Likewise, you need to plug up to the hundred with the increment of five.



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So.



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For the 15 days, forty nine point one, so when you plot these characteristics, toxified character,



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it called the toxified characteristic of a vehicle, we're measuring the statistics.



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We will use this characteristic for merging the different system level simulation, electrical with



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this mechanical model of the vehicle.



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So this talk is generated.



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So, you know, this experiment and Shari'ah result of the task with characteristic of the vehicle in



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terms of local people as well as in terms of plot.



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So it will be exponentially increasing.



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You will realize that it will increase exponentially.



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But this is called the speed characteristic of our speed makeup that can be predicted by this model.



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So this is the output in terms of speed.



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And acceleration performance also we can predict and distance travel, but main important thing, we



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are interested in the actual speed and the acceleration of the vehicle and this talk is generated from



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the electric motor.



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So in that section of the electric drive, we will discuss about the aspect of electrical, motor and



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system level simulation of electric motor that can generate this talk and this talk.



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When applied to the vehicle.



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We can predict the performance of the system of combining the electrical as well as the mechanical systems.



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When we supply the voltage to the electrical system, it will generate the thought that we will see



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the motor and this is applied to the vehicle model and it will result in speed.



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So when we supply the voltage, we will get the speed and the performance that.



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Hope you got that basic idea about the system level simulation of vehicle with the help of Matlab simulation



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model.