Deep reinforcement learning implementation on IC engine idle speed control

Deep reinforcement learning implementation on IC engine idle speed control

Efficient control of automotive engine idle speed is crucial for achieving better fuel economy and smoother engine running. This paper presents a comparison between proportional-integral-derivative (PID) control and Reinforcement Learning (RL) using the Deep Q-Network (DQN) algorithm as a high-level...

Full description

Bibliographic Details
Main Authors: Ibrahim Omran, Ahmed Mostafa, Ahmed Seddik, Mohamed Ali, Mohand Hussein, Youssef Ahmed, Youssef Aly, Mohamed Abdelwahab
Format: Article
Language:English
Published: Elsevier 2024-05-01
Series:Ain Shams Engineering Journal
Subjects:
Engine idle speed control
Reinforcement learning
DQN algorithm
Engine model
PID
Fuel economy
Online Access:http://www.sciencedirect.com/science/article/pii/S2090447924000455

Internet

http://www.sciencedirect.com/science/article/pii/S2090447924000455

Similar Items