CDIO Project 2022
Machine Learning and Adaptive Regulation for Improved Servoperformance
ICE
The majority of cars as of today are still running on a ICE which needs regulation of airflow. This is where the throttle is vital.
Code
To regulate the desired torque, a robust controller is needed.
Improved performance
A successful implementation gives better driveability and improves fuel consumption.
Gallery
Core components during this project and results.
A servo valve which regulates the inflow of air to the engine.
Pocket-sized computer vital for the communication between MATLAB and the throttle.
The main program used for implementation of controller and comunication between the system and throttle.
The team that has carried out this project consist of 7 engineering studets at Linköping University, with a diverse background among us. The constantly changing demands from the outside world puts high demands on the automotive industry. To cope with these demands, the automotive industry needs to be adaptable in many ways. The constantly increasing requirements on emissions creates a demand for new solutions in the engine development.
Therefore, the scope of this project has been to improve the servoperformance of a throttle using adaptive regulation and machine learning.
Project Leader
Hardware
Document
Software
Quality
Information
Hardware
All requirements needed to covered in this project.
Our general plan over the work during the project.
Our pilot study over the project.
All the tests planed.
Documentation over the testing.
Documentation of the results during the project.
User manual to the project.
Poster Presentation.
