Multi-Level Deceleration Planning Based on Reinforcement Learning Algorithm for Autonomous Regenerative Braking of EV
A smart regenerative braking system, which is an advanced driver assistance system of electric vehicles, automatically controls the regeneration torque of the electric motor to brake the vehicle by recognizing the deceleration conditions. Thus, this autonomous braking system can provide driver conve...
Main Authors: | Kyunghan Min, Gyubin Sim, Seongju Ahn, Inseok Park, Seungjae Yoo, Jeamyoung Youn |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-09-01
|
Series: | World Electric Vehicle Journal |
Subjects: | |
Online Access: | https://www.mdpi.com/2032-6653/10/3/57 |
Similar Items
-
Automatic Longitudinal Regenerative Control of EVs Based on a Driver Characteristics-Oriented Deceleration Model
by: Gyubin Sim, et al.
Published: (2019-09-01) -
Deceleration Planning Algorithm Based on Classified Multi-Layer Perceptron Models for Smart Regenerative Braking of EV in Diverse Deceleration Conditions
by: Gyubin Sim, et al.
Published: (2019-09-01) -
Vehicle Deceleration Prediction Model to Reflect Individual Driver Characteristics by Online Parameter Learning for Autonomous Regenerative Braking of Electric Vehicles
by: Kyunghan Min, et al.
Published: (2019-09-01) -
Naturalistic rapid deceleration data: Drivers aged 75 years and older
by: Anna Chevalier, et al.
Published: (2016-12-01) -
An autonomous emergency braking strategy based on non‐linear model predictive deceleration control
by: Hongyuan Mu, et al.
Published: (2023-03-01)