# Vehicle and Engine Simulink Model Engine rpm calculation

• Automotive
• Zain Abbasi
In summary, the conversation discussed the process of designing a Simulink model for HIL testing, which involves calculating requested torque based on throttle angle and then accounting for delays and external loads. The question was raised about the correct approach for finding engine angular speed, with considerations for engine inertia and external loads. Finally, the need to model internal friction to match literature or test bench data was mentioned.

#### Zain Abbasi

Hello Everyone,

I am designing Simulink model for HIL testing. Basic concept:
Input: Throttle angle ----> Injection timing from that I have calculated requested torque (% of max torque)(chekced and correct)
Real torque follows requested torque with delay. (long list of conditions depending on engine design and parameters)
Total torque = Real torque - Internal friction torque (bmep = imep - tfmep)
Now this is the toque I have at crankshaft.

My question
a) Is it correct approach if I integrate this torque and divide it by engine inertia to find engine angular speed. (Torque = Inertia*angular accelaration)?

Consideration: If I do that it would mean that my engine rpm is independant on external load and only on torque request, which is obviously not the case.

b) External loads are calculated using coast down coefficients and gearbox, differential ratio and transmission efficiency. I feel the correct approach would be to create a close loop and subtract external loads from torque transmitted by flywheel and then integrate it to find rpm.

Any suggestions?

Thanks

Last edited:
The angular acceleration will depend on the engine inertia as well as the inertia from any rotating mass connected to the crankshaft (considering gear ratios if any) and, if you move an object like a car for example, you need to consider the mass of the car that is also accelerating as well.

The angular acceleration will also depend on the engine torque minus the reaction torque coming from external loads (again considering gear ratios if any, and drag & rolling resistance acting on a car, if any).

Thank you for your reply. I have followed same approach. As a first step, results are quite okay. Only I have to model internal friction as a function of Toil, Poil and rpm in a way that my final result looks like rpm vs torque curve as seen in literature or from test bench data.

## What is a Simulink model for vehicle and engine rpm calculation?

A Simulink model is a mathematical representation of a system, used to simulate and analyze its behavior. In the context of vehicle and engine rpm calculation, it is a model that uses inputs such as vehicle speed and engine torque to calculate the engine rpm.

## What is the purpose of a Simulink model for vehicle and engine rpm calculation?

The purpose of a Simulink model for vehicle and engine rpm calculation is to accurately predict the engine rpm based on various inputs. This can be used for performance analysis, fuel efficiency optimization, and emissions control.

## How is the Simulink model for vehicle and engine rpm calculation developed?

The Simulink model for vehicle and engine rpm calculation is developed using a combination of physical principles and experimental data. It involves creating mathematical equations and using simulation tools to validate the model and fine-tune its parameters.

## What are the key components of a Simulink model for vehicle and engine rpm calculation?

The key components of a Simulink model for vehicle and engine rpm calculation include the engine model, vehicle dynamics model, and control system. The engine model simulates the behavior of the engine, the vehicle dynamics model simulates the vehicle's motion, and the control system combines these models to calculate the engine rpm.

## What are the benefits of using a Simulink model for vehicle and engine rpm calculation?

Some of the benefits of using a Simulink model for vehicle and engine rpm calculation include faster and more accurate predictions, the ability to test different scenarios and parameters, and the flexibility to make changes and improvements to the model. It also allows for easier integration with other simulation tools and software.