Erfan Abbasi Shahisaraei | Electric Vehicles | Student Research Paper Award

Mr. Erfan Abbasi Shahisaraei | Electric Vehicles | Student Research Paper Award

PhD Student | Tarbiat Modares University | Iran

Mr. Erfan Abbasi Shahisaraei is a mechanical engineering researcher with strong expertise in fatigue life analysis, advanced structural design, and composite and architected materials. Professional experience includes research and engineering roles focused on electric vehicle battery pack design, vibration and shock analysis under international standards, reverse engineering of steelmaking equipment, and structural and fatigue analysis of industrial systems using advanced FEA tools. Research interests span fatigue and dynamic behavior of electric vehicle components, lattice and fiber-reinforced composites, fracture mechanics, and optimization-driven structural design. Research skills include finite element modeling, fatigue assessment, multi-body dynamics, numerical optimization, and engineering simulation using industry-standard software and programming tools. Awards and honors reflect consistent academic and research excellence through competitive projects and peer-reviewed publications. Overall, the work demonstrates a strong integration of theory, simulation, and applied engineering for energy and transportation systems.He has achieved 1 document.


View Research Gate Profile

View Google Scholar Profile

View ORCID Profile

Featured Publication


Numerical Fatigue Life Analysis for Battery Pack of Electric Bus Under Random Vibration


– Iranian Journal of Science and Technology, Transactions of Mechanical Engineering, 2025

Wanke cao | Electric Vehicles | Best Paper Award

Prof. Wanke Cao | Electric Vehicles | Best Paper Award

Director of the Department of In-Vehicle Network Technologies |  Shenzhen Automotive Research Institute (SZART) | China

Prof. Wanke Cao is an established academic and researcher in electric vehicle engineering, with a strong profile spanning summary, professional experience, research interests, research skills, awards and honors, and overall contributions to the field. His professional experience includes long-term academic leadership and research roles in electric vehicle systems, in-vehicle networks, and intelligent automotive technologies, with international research exposure and institutional responsibilities. His research interests focus on networked control of electric vehicles, vehicle dynamics and control, and in-vehicle network technologies. His research skills include modeling and control of vehicle systems, intelligent transportation technologies, embedded and networked automotive systems, and applied engineering research. He has received recognition for sustained research output, academic service, and technical contributions. Overall, his work demonstrates consistent impact on electric vehicle technology development and scholarly advancement. He has acheived 1195 Citations, 69 Documents,16 h-index.

Citation Metrics (Scopus)

1200
900
600
300
0

1,195
Citations

69
Documents

16
h-index

Citations

Documents

h-index

 


View Research Gate Profile

View Scopus Profile

View ORCID Profile

Top 5 Publications

Ayşe Tuğba Yapıcı | Electric Vehicles | Best Research Article Award

Ms. Ayşe Tuğba Yapıcı | Electric Vehicles | Best Research Article Award

Doctoral Researcher  |  Kocaeli University  |  Turkey

Ms. Ayşe Tuğba Yapıcı is a dedicated doctoral researcher whose academic journey is strongly rooted in cutting-edge technologies for electric vehicles, smart energy systems, and intelligent power electronics. She has cultivated significant professional experience through her active involvement in research addressing real-world problems such as electric vehicle charging optimization, grid-integrated charging infrastructures, and advanced modeling of power converter systems. Throughout her career, she has contributed to impactful scientific studies focusing on induction heating systems, charging time prediction using deep learning, and data-driven forecasting on electric vehicle adoption and infrastructure planning. Her research interests include electric vehicle technologies, charging station design, renewable-integrated smart grids, artificial intelligence–based energy forecasting, machine learning and deep learning applications in power systems, and IoT-enhanced smart mobility frameworks. She possesses strong research skills in Python-based deep learning toolkits, MATLAB/Simulink, DigSilent PowerFactory modeling, statistical evaluation metrics, time-series forecasting, optimization algorithms, and performance analysis of intelligent systems. She has published multiple peer-reviewed articles in international SCI/Scopus-indexed journals, delivering innovative research outcomes that offer comprehensive and practical solutions for the sustainable development of electric transportation. Her research achievements include proposing an intelligent deep learning–based framework for EV charging time prediction, integrating spatial–temporal mobility parameters, and enhancing operational efficiency for fast-charging infrastructures. Her work stands out for its interdisciplinary approach and technological significance, supporting the transition toward cleaner mobility, optimized charging networks, and smart energy management. In addition to research excellence, she continues to contribute to academic and scientific communities through conference participation, collaborations, and knowledge dissemination. She aims to advance secure, intelligent, and scalable charging automation systems that support next-generation autonomous electric mobility. Her long-term vision is to shape energy-efficient transportation ecosystems, reduce environmental impacts, and contribute to the global sustainability agenda through innovation and scientific leadership. She has achieved  3 Citations , 2 Documents,  1 h-index.

Featured Publications

Yapıcı, A. T., & Abut, N. (2025, November 23). An intelligent and secure IoT-based framework for predicting charging and travel duration in autonomous electric taxi systems. Applied Sciences.

Yapıcı, A. T., Abut, N., & Yıldırım, A. (2025, October 27). Estimation of future number of electric vehicles and charging stations: Analysis of Sakarya Province with LSTM, GRU and multiple linear regression approaches. Applied Sciences.

Yapıcı, A. T., & Abut, N. (2025, August 21). Geleceğe yönelik elektrikli araç ve şarj istasyonu sayılarının LSTM ve GRU derin öğrenme yöntemleri kullanılarak tahmin edilmesi: Kocaeli ili örneği. Politeknik Dergisi.

Yapıcı, A. T., Abut, N., & Erfidan, T. (2025, April 11). Comparing the effectiveness of deep learning approaches for charging time prediction in electric vehicles: Kocaeli example. Energies.

Yapıcı, A. T., & Abut, N. (2024, September 15). Elektrikli araç şarj istasyonu konum tasarımında, Digsilent yazılımı kullanılarak Kocaeli Üniversitesi Umuttepe Kampüsü için örnek uygulama. Black Sea Journal of Engineering and Science.

Ayşe Tuğba Yapıcı’s research advances intelligent and sustainable electric mobility by integrating deep learning, smart grid technologies, and IoT-based predictive frameworks to optimize charging infrastructure and energy management. Her work supports the transition toward autonomous electric transportation, reducing environmental impacts, improving urban mobility planning, and contributing to global innovation in smart energy systems. She envisions scalable, reliable, and human-centered smart mobility ecosystems that accelerate the adoption of clean transportation worldwide.

Bao Xie | Electric Vehicles | Editorial Board Member

Dr. Bao Xie | Electric Vehicles | Editorial Board Member

lecturer | Hefei University of Technology | China

Dr. Bao Xie is an accomplished researcher and lecturer specializing in Electrical Engineering with a strong academic foundation and extensive experience in renewable energy systems, grid-connected power generation, and inverter stability control. Currently serving as a lecturer and supervisor of master’s candidates at the Hefei University of Technology, he has established a solid reputation in the fields of power electronics, control theory, and grid integration of renewable energy sources. His research primarily focuses on the control and stability of renewable energy grid-connected power systems, addressing challenges related to weak grid conditions, harmonic resonance, and digital control of large-scale photovoltaic (PV) plants. Over the years, Dr. Xie has demonstrated exceptional technical acumen and problem-solving ability, contributing significantly to multiple national and provincial-level research projects, including the Anhui Provincial Natural Science Foundation and the National Key Research and Development Programs. His research skills encompass advanced modeling, control strategy design, resonance analysis, and power conversion optimization, supported by a profound understanding of grid dynamics and inverter interactions. Dr. Xie’s scholarly contributions include over 60 publications in prestigious journals such as IEEE Transactions on Energy Conversion, IET Power Electronics, and International Journal of Electrical Power and Energy Systems, showcasing innovative approaches to improving grid stability and renewable integration. His dedication to academic excellence has earned him recognition as a promising figure in the next generation of electrical engineers, with his work offering impactful insights for sustainable and intelligent energy systems. Through his continuous pursuit of innovation, collaboration, and mentorship, he exemplifies the integration of theory and practical engineering for real-world energy applications. He has achieved 653 Citations, 61 Documents, 15h-index.

Profile:   Scopus

Featured Publications 

  1. Xie, B., Zheng, W., Li, P., Shi, Y., & Su, J. (2025). Stability analysis and admittance reshaping for PQ inverters with different power control methods. International Journal of Electrical Power and Energy Systems.

  2. Xie, B., Zhang, Q., Liu, T., Zhou, L., & Hao, G. (2025). Research on multi-model LQR control strategy for grid-connected inverters under weak grid. Electric Power Systems Research.

  3. Xie, B., Guo, K., Mao, M., Zhou, L., Liu, T., & Zhang, Q. (2025). Optimization of energy storage capacity of village-level microgrid considering the orderly charging of electric vehicles. Sustainable Energy Grids and Networks.

  4. Xie, B., Zhou, L., Liu, T., Zhang, Q., & Hao, G. (2025). Topology and control method of interleaved parallel DC/DC converters with ripple compensation for fuel cell applications. Journal of Power Electronics.

  5. Xie, B., Mao, M., Liu, T., Zhou, L., & Zhang, Q. (2025). State prediction consistency secondary control strategy for microgrids with adaptive virtual impedance. Dianji Yu Kongzhi Xuebao (Electric Machines and Control).

    Dr. Bao Xie’s research advances the stability, efficiency, and intelligence of renewable energy integration within modern power grids. His innovative control strategies for inverters and microgrids foster sustainable energy transitions and resilient smart grid infrastructures. Through interdisciplinary research bridging academia and industry, his work supports global innovation in clean energy technologies and digital power systems.