Loading [MathJax]/extensions/MathZoom.js
Ruchen Huang - IEEE Xplore Author Profile
Access provided by:

MIT Libraries

Sign Out
Access provided by:

MIT Libraries

Sign Out
ADVANCED SEARCH

Author details

< Back

Ruchen Huang

Publications
15
Citations
21
Publications by Year
20212024
Co-Authors:
Show All Co-Authors (27)
Image of author Ruchen Huang

Ruchen Huang

Affiliation

National Engineering Research Center for Electric Vehicles
Beijing Institute of Technology
Beijing, China

Publication Topics

Biography

Ruchen Huang received the B.S. degree in vehicle engineering from the China University of Petroleum (East China), Qingdao, China, in 2020. He is currently working toward the Ph.D. degree in vehicle engineering with the School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China.,His research interests include optimal control theory, machine learning applications, and intelligent electric vehicles.(Based on document published on 21 November 2022).
Publications
15
Citations
21
Publications by Year
20212024
Co-Authors:
Show All Co-Authors (27)
Author's Published Works

Showing 1-15 of 15 results

  • Sort

Filter Results

Show

Sort By

Results

Design and Dynamics Analysis of the Walking System for an Articulated Crawler Tractor

Li Kang;Qicong Su;Ruchen Huang;Hongwen He

2024 International Conference on Electrical and Computer Engineering Researches (ICECER)
Year: 2024 | Conference Paper |
Articulated crawler tractors, with their unique structure and performance, not only have increased capacity compared to traditional tractors but also possess high passing performance and maneuverability. This paper presents the design of the walking systems and a whole-vehicle simulation model for an articulated crawler tractor, enabling research on dynamics simulation. Firstly, the 3D models of t...Show More

Design and Dynamics Analysis of the Walking System for an Articulated Crawler Tractor

Li Kang;Qicong Su;Ruchen Huang;Hongwen He

Year: 2024 | Conference Paper |

Energy Management for Electrified Tracked Vehicles via Improved Soft Actor-Critic Algorithm

Qicong Su;Ruchen Huang;Li Kang;Hongwen He

2024 IEEE Vehicle Power and Propulsion Conference (VPPC)
Year: 2024 | Conference Paper |
Energy management strategies (EMSs) play a crucial role in determining the power distribution of hybrid electric vehicles (HEVs). Recently, deep reinforcement learning (DRL) has emerged as a prominent approach for developing EMSs. This paper proposes a DRL-based EMS for a series hybrid electric tracked vehicle (SHETV) equipped with an enginegenerator set (EGS) and a battery pack to improve fuel ec...Show More

Energy Management for Electrified Tracked Vehicles via Improved Soft Actor-Critic Algorithm

Qicong Su;Ruchen Huang;Li Kang;Hongwen He

Year: 2024 | Conference Paper |

Integrated Speed Planning and Energy Management Optimization for Hybrid Electric Buses in Car-Following Scenarios

Zheng Zhou;Jinda Wu;Zegong Niu;Hongwen He;Ruchen Huang;Yiwei Zhou

2024 12th International Conference on Traffic and Logistic Engineering (ICTLE)
Year: 2024 | Conference Paper |
The enhancing driving economy is a crucial pathway for promoting the development of electrified vehicles, wherein speed planning and energy flow management are two major ways to reduce energy consumption. Different from conventional solutions, this study proposes a coherent integrated methodology for simultaneously regulating the longitudinal speed and powertrain statues based on an improved model...Show More

Integrated Speed Planning and Energy Management Optimization for Hybrid Electric Buses in Car-Following Scenarios

Zheng Zhou;Jinda Wu;Zegong Niu;Hongwen He;Ruchen Huang;Yiwei Zhou

Year: 2024 | Conference Paper |

Energy Management Strategy Based on an Improved TD3 Reinforcement Algorithm with Novel Experience Replay

Zegong Niu;Ruchen Huang;Hongwen He;Zhiqiang Zhou;Qicong Su

2023 IEEE Vehicle Power and Propulsion Conference (VPPC)
Year: 2023 | Conference Paper |
The energy management strategy (EMS) plays an important part in the systematic control of hybrid electric vehicles (HEVs). In recent years, the EMS based on deep reinforcement learning (DRL) receives more attention. This paper proposes an EMS based on TD3 deep reinforcement learning algorithm with novel experience replay. The experience replay is introduced to select samples via an evaluation netw...Show More

Energy Management Strategy Based on an Improved TD3 Reinforcement Algorithm with Novel Experience Replay

Zegong Niu;Ruchen Huang;Hongwen He;Zhiqiang Zhou;Qicong Su

Year: 2023 | Conference Paper |

A Data-Driven Energy Management Strategy for Series Hybrid Electric Tracked Vehicle Based on Power Coordinated Control

Qicong Su;Ruchen Huang;Hongwen He;Xuefeng Han;Zegong Niu;Zhiqiang Zhou

2023 IEEE Vehicle Power and Propulsion Conference (VPPC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
The power distribution and fuel economy of hybrid electric vehicles are greatly influenced by energy management strategies (EMSs). In this paper, a series hybrid electric tracked vehicle (SHETV) with an independent dual-side drive and a full-wave rectification is served as the research object. The EMS based on dynamic programming (DP) is first constructed to be used as the global optimal benchmark...Show More

A Data-Driven Energy Management Strategy for Series Hybrid Electric Tracked Vehicle Based on Power Coordinated Control

Qicong Su;Ruchen Huang;Hongwen He;Xuefeng Han;Zegong Niu;Zhiqiang Zhou

Year: 2023 | Conference Paper |

Intelligent Energy Management for Fuel Cell Bus Based on Enhanced Soft Actor-Critic Algorithm

Ruchen Huang;Zegong Niu;Qicong Su;Hongwen He;Zheng Zhou;Zhiqiang Zhou

2023 IEEE Vehicle Power and Propulsion Conference (VPPC)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Energy management strategies (EMSs) directly affect the fuel economy of hybrid electric vehicles, and deep reinforcement learning (DRL) has become the mainstream method for energy management in recent years. This paper proposes an intelligent DRL-based EMS for an urban fuel cell bus (FCB) powered by both fuel cell and battery to improve the energy efficiency of the FCB. To begin, an enhanced soft ...Show More

Intelligent Energy Management for Fuel Cell Bus Based on Enhanced Soft Actor-Critic Algorithm

Ruchen Huang;Zegong Niu;Qicong Su;Hongwen He;Zheng Zhou;Zhiqiang Zhou

Year: 2023 | Conference Paper |

Lithium-Ion battery remaining useful life prediction method concerning temperature-influenced charging data

Sikai Gong;Hongwen He;Xuyang Zhao;Yiwen Shou;Ruchen Huang;Hongwei Yue

2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
Year: 2023 | Conference Paper |
Developing the remaining useful life (RUL) prediction technology for lithium-ion batteries can effectively provide information for battery maintenance and diagnosis. Although there has been some development in battery RUL prediction methods like model-based methods and data-driven methods, the influence of temperature on battery system is rarely considered. Besides, in the actual operation of the ...Show More

Lithium-Ion battery remaining useful life prediction method concerning temperature-influenced charging data

Sikai Gong;Hongwen He;Xuyang Zhao;Yiwen Shou;Ruchen Huang;Hongwei Yue

Year: 2023 | Conference Paper |

A Calculation-Efficient Predictive Energy Management Strategy for Fuel Cell Hybrid Electric Bus based on Improved Optimization Solver

Miaojue Gao;Hongwen He;Ruchen Huang

2023 IEEE 18th Conference on Industrial Electronics and Applications (ICIEA)
Year: 2023 | Conference Paper |
This paper proposes a calculation-efficient predictive energy management strategy (EMS) for a fuel cell hybrid electric bus (FCHEB) based on an improved optimization solver. A deep neural network (DNN) based speed predictor is trained using real bus driving dataset and then adopted to predict the bus speed. After that, the direct collocation method is applied to transform the energy management pro...Show More

A Calculation-Efficient Predictive Energy Management Strategy for Fuel Cell Hybrid Electric Bus based on Improved Optimization Solver

Miaojue Gao;Hongwen He;Ruchen Huang

Year: 2023 | Conference Paper |

From Grayscale Image to Battery Aging Awareness—A New Battery Capacity Estimation Model With Computer Vision Approach

Xuyang Zhao;Hongwen He;Jianwei Li;Zhongbao Wei;Ruchen Huang;Man Shi

IEEE Transactions on Industrial Informatics
Year: 2023 | Volume: 19, Issue: 8 | Journal Article |
Cited by: Papers (8)
Accurate detection of capacity degradation is critical to the safe and efficient utilization of battery systems. Many data-driven capacity estimators were proposed based on emerging intelligent algorithms, but their accuracy depends on the data of complete charged/discharged process and complex algorithm structures. This article developed a computer vision (CV)-based method, constructing battery m...Show More

From Grayscale Image to Battery Aging Awareness—A New Battery Capacity Estimation Model With Computer Vision Approach

Xuyang Zhao;Hongwen He;Jianwei Li;Zhongbao Wei;Ruchen Huang;Man Shi

Year: 2023 | Volume: 19, Issue: 8 | Journal Article |

Research on Shift Control Strategy of Hybrid Electric Vehicle Based on an Improved DCT Configuration

Hu Julin;Yuji Wei;Hongwen He;Ruchen Huang;Jie Xing

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)
Year: 2022 | Conference Paper |
In this paper, an improved shift without power interruption control strategy is proposed for a new hybrid power transmission system composed of a planetary gear and an improved DCT transmission. In the conventional mode, the power of the engine and the motor are coupled through the planetary row to drive the vehicle in parallel; In the improved mode, the engine and the motor respectively drive thr...Show More

Research on Shift Control Strategy of Hybrid Electric Vehicle Based on an Improved DCT Configuration

Hu Julin;Yuji Wei;Hongwen He;Ruchen Huang;Jie Xing

Year: 2022 | Conference Paper |

Research on Shifting Strategy of Hybrid Electric Vehicle Based on Dynamic Programming Algorithm

Yuji Wei;Hu Julin;Hongwen He;Ruchen Huang;Jie Xing;Miaojue Gao

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)
Year: 2022 | Conference Paper |
In this paper, for a hybrid power transmission system composed of a planetary gear mechanism and an improved DCT transmission, the vehicle dynamics model, energy management strategy and torque distribution strategy are established through MATLAB, and two-parameter optimal economical shifting law is obtained by analytical method. By constructing a global optimization problem and solving it through ...Show More

Research on Shifting Strategy of Hybrid Electric Vehicle Based on Dynamic Programming Algorithm

Yuji Wei;Hu Julin;Hongwen He;Ruchen Huang;Jie Xing;Miaojue Gao

Year: 2022 | Conference Paper |

A deep learning-based power battery capacity estimation model assisted with feature vector construction

Xuyang Zhao;Hongwen He;Ruchen Huang;Jingwei Dou;Yunlong Wang;Chunchun Jia

2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
This study aims to answer the key question on how to detect the capacity degradation of the power batteries in electric vehicles (EVS) with emerging intelligent methods. Focusing on the random and incomplete charging process in actual EVs usage, the new estimation method only needs a specific charging current segment rather than data from the whole charging process for model training and estimatio...Show More

A deep learning-based power battery capacity estimation model assisted with feature vector construction

Xuyang Zhao;Hongwen He;Ruchen Huang;Jingwei Dou;Yunlong Wang;Chunchun Jia

Year: 2022 | Conference Paper |

A Real-time Predictive Energy Management Strategy for Power-split Plug-in Hybrid Electric Bus

Ruchen Huang;Hongwen He;Xiangfei Meng

2021 International Conference on Industrial Electronics Research and Applications (ICIERA)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
This paper proposes a real-time predictive energy management strategy (EMS) for a power-split plug-in hybrid electric bus (PHEB) to improve fuel economy by decreasing the total operation cost of fuel and electricity. Firstly, a two- dimensional (2-D) velocity prediction method is adopted to improve the accuracy of the prediction. Then, an online optimal controller is designed to distribute power f...Show More

A Real-time Predictive Energy Management Strategy for Power-split Plug-in Hybrid Electric Bus

Ruchen Huang;Hongwen He;Xiangfei Meng

Year: 2021 | Conference Paper |

Energy Management Strategy for Plug-in Hybrid Electric Bus based on Improved Deep Deterministic Policy Gradient Algorithm with Prioritized Replay

Ruchen Huang;Hongwen He;Xiangfei Meng;Yong Wang;Renzong Lian;Yuji Wei

2021 IEEE Vehicle Power and Propulsion Conference (VPPC)
Year: 2021 | Conference Paper |
Cited by: Papers (6)
Deep reinforcement learning-based energy management strategy (EMS) is a state-of-art technology for hybrid electric vehicles (HEVs). This paper proposes a novel EMS based on improved deep deterministic policy gradient (DDPG) algorithm with prioritized replay for a power-split plug-in hybrid electric bus (PHEB) to improve the fuel economy of PHEB as well as the learning efficiency of DDPG. Firstly,...Show More

Energy Management Strategy for Plug-in Hybrid Electric Bus based on Improved Deep Deterministic Policy Gradient Algorithm with Prioritized Replay

Ruchen Huang;Hongwen He;Xiangfei Meng;Yong Wang;Renzong Lian;Yuji Wei

Year: 2021 | Conference Paper |

A Novel Hierarchical Predictive Energy Management Strategy for Plug-in Hybrid Electric Bus Combined with Deep Reinforcement Learning

Ruchen Huang;Hongwen He;Xiangfei Meng;Menglin Li

2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
This paper proposes a novel hierarchical predictive energy management strategy combined with deep reinforcement learning (DRL) for a plug-in hybrid electric bus (PHEB). Firstly, a real-world speed profile is used to train the DDPG algorithm to generate the state of charge (SOC) reference intelligently. Then, a hierarchical model predictive control (MPC) strategy is designed to predict the velocity...Show More

A Novel Hierarchical Predictive Energy Management Strategy for Plug-in Hybrid Electric Bus Combined with Deep Reinforcement Learning

Ruchen Huang;Hongwen He;Xiangfei Meng;Menglin Li

Year: 2021 | Conference Paper |

IEEE Account

Purchase Details

Profile Information

Need Help?

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.