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Deep reinforcement learning based energy management strategies for electrified vehicles: Recent advances and perspectives
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 …
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
As a hybrid electric vehicle (HEV) key control technology, intelligent energy management
strategies (EMSs) directly affect fuel consumption. Investigating the robustness of EMSs to …
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
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 …
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
A supervisory control strategy, including dynamic control supervisor, handling-stability
controller, energy efficiency controller, and coordinated torque allocator, is proposed for …
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
This article proposes a computationally efficient path-following control strategy of
autonomous electric vehicles (AEVs) with yaw motion stabilization. First, the nonlinear …
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
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 …
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
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 …
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
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 …
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 …
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
Distributed drive electric vehicles (DDEVs) eliminate the complex drivetrain. The
independently driven in-wheel motors also endow the vehicle with more ability for improving …
independently driven in-wheel motors also endow the vehicle with more ability for improving …