AUTHOR PROFILE
SCOPUS
ORCID
EARLY ACADEMIC PURSUITS
Zhijia Huang embarked on his academic journey at Shenzhen University, focusing on battery technology during his undergraduate and master's programs. His master's research concentrated on battery modeling and state estimation, significantly enhancing his expertise in complex system analysis and data processing. This period laid a foundational understanding of battery technologies, pivotal to his academic trajectory.
PROFESSIONAL ENDEAVORS
Transitioning to a doctoral program at the Beijing Institute of Technology, Huang shifted his research focus toward charging demand prediction and the planning of charging facilities within the realm of intelligent connected vehicles and electric drive, specifically targeting smart grid subdivisions. His work aims to tackle the challenges introduced by the increasing prevalence of electric vehicles (EVs), emphasizing sustainable energy solutions and the optimization of charging infrastructure layout.
Huang's research primarily addresses the forecasting of urban charging loads and planning for charging infrastructure to accommodate the growing demands of EVs. By analyzing operational data from private passenger EVs in Beijing, he has developed a comprehensive model that considers travel patterns, urban road networks, and existing charging facilities. This model aims to predict the number of charging EVs and the required charging power with high accuracy, laying groundwork for optimal charging infrastructure planning.
IMPACT AND INFLUENCE
The urban charging load forecasting model proposed by Huang demonstrates significant potential for influencing the planning and development of EV charging infrastructure. With its ability to predict charging demands accurately, the model serves as a critical tool for urban planners and energy network developers, guiding the strategic deployment of charging facilities to meet future needs efficiently.
ACADEMIC CITES
Huang's scholarly work, comprising 8 journal publications indexed in SCI and SCIE with a cumulative impact factor of 36.4 and an H-index of 6, underscores his contributions to the field. His research outputs are well-cited, with 127 citations in Scopus/Web of Science, illustrating the recognition and relevance of his work within the academic community.
LEGACY AND FUTURE CONTRIBUTIONS
As Huang continues his research in intelligent connected vehicles and smart grid technology, his efforts are poised to leave a lasting impact on the development of sustainable energy solutions and the integration of EVs into urban environments. His focus on charging demand forecasting and infrastructure planning addresses key challenges in the transition to greener transportation options, setting a foundation for future innovations in the field.
NOTABLE PUBLICATIONS
Mechanical vibration modeling and characterization of a plastic-cased lithium-ion battery 2022(10)
Parallel-connected battery module modeling based on physical characteristics in multiple 2022(6)
State of charge estimation of lithium-ion batteries based on cubature Kalman filters 2022(37)
State-of-charge estimation tolerant of battery aging based on a physics-based model 2021(70)
Performance analysis and modeling of three energy storage devices for electric vehicle 2020(9)