Deep reinforcement learning based energy management strategies for electrified vehicles: Recent advances and perspectives

H He, X Meng, Y Wang, A Khajepour, X An… - … and Sustainable Energy …, 2024 - Elsevier
Electrified vehicles provide an effective solution to address the unfavorable impacts of fossil
fuel use in the transportation sector. Energy management strategy (EMS) is the core …

High robustness energy management strategy of hybrid electric vehicle based on improved soft actor-critic deep reinforcement learning

W Sun, Y Zou, X Zhang, N Guo, B Zhang, G Du - Energy, 2022 - Elsevier
As a hybrid electric vehicle (HEV) key control technology, intelligent energy management
strategies (EMSs) directly affect fuel consumption. Investigating the robustness of EMSs to …

Real-time predictive energy management of plug-in hybrid electric vehicles for coordination of fuel economy and battery degradation

N Guo, X Zhang, Y Zou, L Guo, G Du - Energy, 2021 - Elsevier
This paper proposes a real-time predictive energy management strategy (PEMS) of plug-in
hybrid electric vehicles for coordination control of fuel economy and battery lifetime …

A supervisory control strategy of distributed drive electric vehicles for coordinating handling, lateral stability, and energy efficiency

N Guo, X Zhang, Y Zou, B Lenzo, G Du… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
A supervisory control strategy, including dynamic control supervisor, handling-stability
controller, energy efficiency controller, and coordinated torque allocator, is proposed for …

A computationally efficient path-following control strategy of autonomous electric vehicles with yaw motion stabilization

N Guo, X Zhang, Y Zou, B Lenzo… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article proposes a computationally efficient path-following control strategy of
autonomous electric vehicles (AEVs) with yaw motion stabilization. First, the nonlinear …

Electric vehicle optimum charging-discharging scheduling with dynamic pricing employing multi agent deep neural network

B Aljafari, PR Jeyaraj, AC Kathiresan… - Computers and Electrical …, 2023 - Elsevier
Abstract Electric Vehicles (EVs) are environmentally friendly. Extensive progress makes EVs
popularly deployed and adopted. Once EVs are connected to the smart grid, EVs can act as …

Predictive energy management of fuel cell plug-in hybrid electric vehicles: A co-state boundaries-oriented PMP optimization approach

N Guo, W Zhang, J Li, Z Chen, J Li, C Sun - Applied Energy, 2024 - Elsevier
This paper proposes a predictive energy management strategy of FC PHEV based on PMP
and co-state boundaries. The model predictive control (MPC) problem is established and …

Energy management for a hybrid electric vehicle based on prioritized deep reinforcement learning framework

G Du, Y Zou, X Zhang, L Guo, N Guo - Energy, 2022 - Elsevier
A novel deep reinforcement learning (DRL) control framework for the energy management
strategy of the series hybrid electric tracked vehicle (SHETV) is proposed in this paper …

Towards longitudinal and lateral coupling control of autonomous vehicles using offset free MPC

L Ge, Y Zhao, F Ma, K Guo - Control Engineering Practice, 2022 - Elsevier
Abstract Model predictive control (MPC) is widely used in the motion control of autonomous
vehicles. However, the conventional MPC relies on an accurate model and cannot achieve …

A robust dynamic game-based control framework for integrated torque vectoring and active front-wheel steering system

J Liang, Y Lu, F Wang, G Yin, X Zhu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Distributed drive electric vehicles (DDEVs) eliminate the complex drivetrain. The
independently driven in-wheel motors also endow the vehicle with more ability for improving …