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Energies
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Hybrid Electric Powertrain System Modelling and Control
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Hybrid Electric Powertrain System Modelling and Control

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "E: Electric Vehicles".

Deadline for manuscript submissions: 10 September 2025 | Viewed by 1607

Special Issue Editors

Prof. Dr. Jiaqiang E

grade E-Mail Website
Guest Editor
College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
Interests: combustion & micro-combustion; biodiesel combustion; micro-thermophotovoltaic power generators; after-treatment system of automotive systems; battery thermal management system
Special Issues, Collections and Topics in MDPI journals
Dr. Bolan Liu

E-Mail Website
Guest Editor
School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: HEV modelling and control; powertrain control and PHM

Special Issue Information

Dear Colleagues,

The hybrid electric powertrain (HEP) is undoubtedly one of the main power systems used for vehicular application to achieve carbon peaking and carbon neutrality goals. Particularly, in recent years, HEPs have presented a situation where various types of HEPs have coexisted for different applications.

Although the systems are different, the composition and operation mode of HEPs are becoming more complex, as a common technology trend. In order to achieve more efficient HEPs, modelling and control are considering to be the main measures. The objective of this Special Issue is to promote the academic achievements in this field.

Modelling and control are important aspects of system research. Modelling can be tailored to different application scenarios, and modelling for control is usually a one-dimensional model that includes modules such as engines, motors, batteries, and controllers. After the model is established and verified, it can serve as the basic object for subsequent control. Control has always been the core of hybrid power system research, including energy management, fault diagnosis, health management, and other dimensions. The algorithms used have evolved from ordinary classical control to modern control and intelligent control, which is an important aspect of the development of hybrid power technology.

Based on the above, this Special Issue will collect reviews and research articles on various aspects of hybrid power modelling and control. We welcome submissions from research institutions to promote the development of hybrid power technology.

Prof. Dr. Jiaqiang E
Dr. Bolan Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hybrid electric powertrain
  • modelling
  • control
  • vehicle system dynamics

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Published Papers (1 paper)

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Research

26 pages, 5455 KiB  
Article
Degradation Diagnosis and Control Strategy for a Diesel Hybrid Powertrain Considering State of Health
by Jingxian Tang, Bolan Liu, Wenhao Fan, Dawei Zhong and Liang Liu
Energies 2024, 17(21), 5413; https://doi.org/10.3390/en17215413 - 30 Oct 2024
Viewed by 1199
Abstract
Hybrid electric vehicles (HEV) are a practical choice for energy saving in the transportation field. Degradation diagnosis (DD) is one of the main methods to guarantee system robustness. However, the classical DD methods cannot meet the requirements of HEV due to their system [...] Read more.
Hybrid electric vehicles (HEV) are a practical choice for energy saving in the transportation field. Degradation diagnosis (DD) is one of the main methods to guarantee system robustness. However, the classical DD methods cannot meet the requirements of HEV due to their system complexity. In this study, a novel Prognostics and Health Management (PHM) study was conducted to face these challenges. Firstly, a physical P2 HEV model with a rule-based controller was built, and its diesel engine sub-model was simplified by a neural network (NN) to ensure real-time performance of the degradation prognostics. Secondly, a degradation prognostics method based on gray relation analysis–principal component analysis (GRA-PCA) was illustrated, which could confirm degradation 2 s after the health index fell below the threshold. Finally, a degradation tolerance strategy based on long short term memory–model predictive control (LSTM-MPC) was performed to optimize vehicle speed tracing with minimal energy consumption and was validated by three cases. The result shows that the energy consumption stayed nearly unchanged for the engine degradation case. For the battery degradation case, the tracing error was reduced by 11.7% with 4.3% more energy consumption. For combined degradation, the strategy achieved a 12.3% tracing error reduction with 3.7% more energy consumption. The suggested PHM method guaranteed vehicle power performance under degradation situations. Full article
(This article belongs to the Special Issue Hybrid Electric Powertrain System Modelling and Control)
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