An efficient multi-objective hierarchical energy management strategy for plug-in hybrid electric vehicle in connected scenario

Article Chemistry, Physical

Co-optimization method of speed planning and energy management for fuel cell vehicles through signalized intersections

Xiaodong Wei et al.

Summary: This paper proposes a method for improving speed planning and energy management of fuel cell vehicles when passing through multiple signalized intersections, using real-time algorithms to achieve significant fuel savings performance.

JOURNAL OF POWER SOURCES (2022)

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Article Green & Sustainable Science & Technology

The role and application of convex modeling and optimization in electrified vehicles

Yapeng Li et al.

Summary: Component sizing and energy management are crucial for minimizing vehicle costs and maximizing energy efficiency in electrified vehicles. Hierarchical optimization framework and convex optimization methods are effective approaches to tackle these challenges.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)

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Review Green & Sustainable Science & Technology

A review of reinforcement learning based energy management systems for electrified powertrains: Progress, challenge, and potential solution

Akhil Hannegudda Ganesh et al.

Summary: This article discusses the impact of internal combustion engine-powered automobiles on climate change and the progress of electrified powertrains, focusing on the application of Reinforcement Learning (RL) based algorithms in the field. It reviews the recent research and potential solutions for challenges in the area of RL-based EMS.

RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)

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Article Engineering, Electrical & Electronic

Sine Resistance Network-Based Motion Planning Approach for Autonomous Electric Vehicles in Dynamic Environments

Tenglong Huang et al.

Summary: This article proposes a motion planning approach for autonomous electric vehicles that generates a smooth planned path based on surrounding information and predicts collision risks. Co-simulation results prove the advantages and feasibility of this method.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2022)

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Article Energy & Fuels

Effect of parallel connection topology on air-cooled lithium-ion battery module: Inconsistency analysis and comprehensive evaluation

Changlong Li et al.

Summary: The study analyzes the influence of connection design on the performance of lithium-ion battery modules and provides a comprehensive performance evaluation of different connection topologies through simulation.

APPLIED ENERGY (2022)

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Article Thermodynamics

Energy management strategy for power-split plug-in hybrid electric vehicle based on MPC and double Q-learning

Zheng Chen et al.

Summary: This paper proposes an energy management strategy based on double Q-learning for plug-in hybrid electric vehicles to allocate power between multiple power sources. By establishing an effective offline learning controller and using a neural network to predict vehicle speed, the proposed strategy achieves superior fuel economy while adapting to different state of charge reference trajectories.

ENERGY (2022)

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Article Engineering, Electrical & Electronic

Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) for the HEVs With a Near-Optimal Equivalent Factor Considering Driving Conditions

Kyunghwan Choi et al.

Summary: In this study, a novel energy management strategy for hybrid electric vehicles (HEVs) is proposed, which considers actual driving conditions to provide near-optimal performance. The strategy defines a near-optimal equivalent factor condition and presents an iterative scheme to adjust this condition. It shows better adaptability to changes in the driving conditions with a smaller loss of optimality.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2022)

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Article Chemistry, Physical

Predictive co-optimization of speed planning and powertrain energy management for electric vehicles driving in traffic scenarios: Combining strengths of simultaneous and hierarchical methods

Xingyu Zhou et al.

Summary: In this study, a simultaneous method and a hierarchical method are developed for active speed planning and powertrain energy management strategy. A modified hierarchical method is proposed by modifying the decoupling strategy of the hierarchical method, achieving similar energy saving effectiveness and high computational efficiency compared to the simultaneous method.

JOURNAL OF POWER SOURCES (2022)

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Article Thermodynamics

Deep reinforcement learning and reward shaping based eco-driving control for automated HEVs among signalized intersections

Jie Li et al.

Summary: In this study, a deep reinforcement learning-based eco-driving control strategy is proposed to optimize the fuel economy, driving safety, and travel efficiency of automated hybrid electric vehicles in a connected traffic environment with signalized intersections. The method utilizes a twin-delayed deep deterministic policy gradient agent to plan vehicle speed in real-time, and transforms the multi-objective optimization function into the value function of the deep reinforcement learning algorithm. The proposed strategy is verified in a real road traffic environment and demonstrates significant reduction in fuel consumption while satisfying traffic lights and safety rules, showing feasibility for real-time application.

ENERGY (2022)

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Article Thermodynamics

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

Ningyuan Guo et al.

Summary: This paper proposes a real-time predictive energy management strategy for plug-in hybrid electric vehicles, which coordinates fuel economy and battery lifetime through velocity prediction and SOC reference generator, formulates a model predictive control problem for cost minimization, and utilizes the C/GMRES algorithm to handle real-time optimization of engine power command. Numerical simulations demonstrate the effectiveness of this strategy in minimizing fuel consumption and restricting battery aging, showing superior solving quality and real-time applicability compared to other algorithms.

ENERGY (2021)

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Article Automation & Control Systems

Energy Management Strategy for Plug-in-Hybrid Electric Vehicles Based on Predictive PMP

Roland Schmid et al.

Summary: This article introduces an energy management strategy for parallel plug-in-hybrid electric vehicles based on Pontryagin's minimum principle, utilizing journey prediction data obtained from a series-production navigation unit. The novel solution method proposed in this work effectively deals with singular controls and achieves considerable energy consumption savings of 5.29% compared to a benchmark control strategy.

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2021)

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Article Engineering, Electrical & Electronic

Integrated Approximate Dynamic Programming and Equivalent Consumption Minimization Strategy for Eco-Driving in a Connected and Automated Vehicle

Shreshta Rajakumar Deshpande et al.

Summary: Recent advancements in V2X communication and onboard computing power have enabled the development of a novel and computationally efficient algorithm for optimizing velocity planning and energy management in hybrid electric vehicles. A multi-layer hierarchical control architecture is proposed, and the algorithm embeds Equivalent Consumption Minimization Strategy into Dynamic Programming to obtain a sub-optimal solution close to the global optimum at a fraction of the computational cost. The algorithm is further converted into a Model Predictive Control framework using principles of Approximate Dynamic Programming for causal, real-time implementation, benchmarked against a global optimal solution obtained with Dynamic Programming for different scenarios.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

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Article Energy & Fuels

Pontryagin ' s minimum principle based fuzzy adaptive energy management for hybrid electric vehicle using real-time traffic information

Dehua Shi et al.

Summary: This paper proposes a novel fuzzy adaptive method for the PMP-based optimal energy management strategy of hybrid electric vehicles, utilizing real-time traffic information and neural network prediction to improve fuel economy and battery charging sustainability. The proposed strategy outperforms traditional methods in various driving cycles.

APPLIED ENERGY (2021)

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Article Thermodynamics

An improved MPC-based energy management strategy for hybrid vehicles using V2V and V2I communications

Hongwen He et al.

Summary: This paper proposes an improved MPC framework for the EMS of PHEB, aiming to achieve optimal energy distribution with increased prediction accuracy and optimized speed sequences. The speed prediction accuracy is improved between two traffic intersections using the PSO method, while the optimal speed sequence is planned in advance when passing through a traffic intersection.

ENERGY (2021)

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Article Automation & Control Systems

ADMM for Exploiting Structure in MPC Problems

Felix Rey et al.

Summary: The study focuses on utilizing the ADMM algorithm in a model predictive control environment to exploit problem structure, decomposing dynamics using virtual subsystems and virtual inputs, and introducing subsystem individual penalty parameters and optimal selection techniques. A new measure of system structure called separation tendency is proposed, with the method showing characteristics such as favorable computational complexity scaling with problem size, high parallelizability, adaptability, and improvement in overall performance even in a single-thread implementation. A simulation study for cascade systems is presented, comparing the new method to conventional ADMM.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2021)

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Article Engineering, Electrical & Electronic

Improving Ride Comfort and Fuel Economy of Connected Hybrid Electric Vehicles Based on Traffic Signals and Real Road Information

Xiaolin Tang et al.

Summary: The proposed MOHO strategy improves riding comfort and fuel economy through speed planning optimization and energy management.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

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Article Thermodynamics

Guided model predictive control for connected vehicles with hybrid energy systems

Qingyun Min et al.

Summary: This paper introduces a novel energy management strategy for connected vehicles, combining supervised learning and model predictive control to achieve a globally optimal solution and energy saving effect.

ENERGY (2021)

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Article Engineering, Electrical & Electronic

Enhanced Eco-Approach Control of Connected Electric Vehicles at Signalized Intersection With Queue Discharge Prediction

Haoxuan Dong et al.

Summary: This study introduces an enhanced eco-approach control strategy to improve energy efficiency at signalized intersections by predicting the movement of vehicle queues. Through a hierarchical framework and numerical simulations, it is shown that the EEAC strategy can effectively enhance energy utilization efficiency.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

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Article Engineering, Electrical & Electronic

An Improved Energy Management Strategy for Hybrid Electric Vehicles Integrating Multistates of Vehicle-Traffic Information

Hongwen He et al.

Summary: This study proposes a cyber-physical system (CPS)-based energy management strategy (EMS) using deep reinforcement learning (DRL) in hybrid electric vehicles (HEVs). The results show significant fuel economy improvement and verify the effectiveness of the proposed EMS in different types of vehicles.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2021)

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Article Energy & Fuels

Multi-mode predictive energy management for fuel cell hybrid electric vehicles using Markov driving pattern recognizer

Yang Zhou et al.

APPLIED ENERGY (2020)

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Article Energy & Fuels

Energy management of hybrid vehicles with state constraints: A penalty and implicit Hamiltonian minimization approach

Marcelino Sanchez et al.

APPLIED ENERGY (2020)

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Article Automation & Control Systems

A Motion Planning and Tracking Framework for Autonomous Vehicles Based on Artificial Potential Field Elaborated Resistance Network Approach

Yanjun Huang et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2020)

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Article Engineering, Electrical & Electronic

A Novel Local Motion Planning Framework for Autonomous Vehicles Based on Resistance Network and Model Predictive Control

Yanjun Huang et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2020)

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Article Engineering, Electrical & Electronic

Look-Ahead Prediction-Based Real-Time Optimal Energy Management for Connected HEVs

Fuguo Xu et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2020)

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Article Green & Sustainable Science & Technology

A real-time blended energy management strategy of plug-in hybrid electric vehicles considering driving conditions

Zhenzhen Lei et al.

JOURNAL OF CLEANER PRODUCTION (2020)

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Article Engineering, Electrical & Electronic

Multiobjective Co-Optimization of Cooperative Adaptive Cruise Control and Energy Management Strategy for PHEVs

Yinglong He et al.

IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION (2020)

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Article Energy & Fuels

Coordinated management of connected plug-in hybrid electric buses for energy saving, inter-vehicle safety, and battery health

Shaobo Xie et al.

APPLIED ENERGY (2020)

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Article Energy & Fuels

Longitudinal autonomous driving based on game theory for intelligent hybrid electric vehicles with connectivity

Shuo Cheng et al.

APPLIED ENERGY (2020)

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Article Energy & Fuels

Energy management strategies comparison for a parallel full hybrid electric vehicle using Reactivity Controlled Compression Ignition combustion

Antonio Garcia et al.

APPLIED ENERGY (2020)

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Article Green & Sustainable Science & Technology

Reducing gasoline consumption in mixed connected automated vehicles environment: A joint optimization framework for traffic signals and vehicle trajectory

Zhihong Yao et al.

JOURNAL OF CLEANER PRODUCTION (2020)

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Article Engineering, Electrical & Electronic

Real-Time Model Predictive Powertrain Control for a Connected Plug-In Hybrid Electric Vehicle

Joseph Oncken et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2020)

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Velocity prediction and profile optimization based real-time energy management strategy for Plug-in hybrid electric buses

Zhendong Zhang et al.

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Cloud computing-based real-time global optimization of battery aging and energy consumption for plug-in hybrid electric vehicles

Yi Zhang et al.

JOURNAL OF POWER SOURCES (2020)

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A novel strategy for power sources management in connected plug-in hybrid electric vehicles based on mobile edge computation framework

Yuanjian Zhang et al.

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Stochastic model predictive control for energy management of power-split plug-in hybrid electric vehicles based on reinforcement learning

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Energy Management in Plug-In Hybrid Electric Vehicles: Convex Optimization Algorithms for Model Predictive Control

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IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2020)

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Real-Time Speed Trajectory Planning for Minimum Fuel Consumption of a Ground Vehicle

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Pontryagin's Minimum Principle based model predictive control of energy management for a plug-in hybrid electric bus

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A Two-Level MPC for Energy Management Including Velocity Control of Hybrid Electric Vehicles

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An efficient multi-objective hierarchical energy management strategy for plug-in hybrid electric vehicle in connected scenario

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