Abdelsalam Ahmed | Engineering | Best Paper Award

Best Paper Award

Abdelsalam Ahmed
Affiliation Tanta University
Country Egypt
Scopus ID 56311161000
Documents 41
Citations 1,115
h-index 13
Subject Area Engineering
Event International Research Excellence and Best Paper Awards
ORCID 0000-0002-0854-4411

Abdelsalam Ahmed

Abdelsalam Ahmed of the Faculty of Engineering, Tanta University, Egypt, is recognized with the Best Paper Award for research in Engineering. His recognized paper,“Integration and Validation of an Embedded Electric Drive System for EV Conversion Kits: A Practical Industrial Case Study”focuses on the integration and validation of embedded electric-drive technology for electric vehicle conversion applications. His broader research activities include electric vehicles, hybrid electric vehicles, electrical drive systems, power electronics, advanced control, and energy-storage technologies.

Abstract

This article recognizes Abdelsalam Ahmed with the Best Paper Award for research in Engineering. His recognized work,“Integration and Validation of an Embedded Electric Drive System for EV Conversion Kits: A Practical Industrial Case Study”,addresses the engineering integration and validation of an embedded electric-drive system for electric vehicle conversion applications.The research is situated within the broader field of electric vehicle propulsion, where successful vehicle electrification requires coordination among electric machines, power-electronic converters, embedded control, energy storage, and vehicle-level operation.Ahmed’s related research includes electric vehicle drive systems and advanced control methods.  [1].

Keywords

Best Paper Award, Abdelsalam Ahmed, Engineering, Electric Vehicles, EV Conversion Kits, Embedded Electric Drive, Electric Drive Systems, EV Powertrain, Electric Motors, Power Electronics, Motor Control, Vehicle Electrification, Hybrid Electric Vehicles, Electrical Machines, Model Predictive Control, Energy Storage, Battery Systems, Vehicle Validation, EV Technology, Sustainable Mobility.

Introduction

Electric vehicle conversion is an important engineering pathway for applying electric propulsion technologies to existing vehicle platforms. The conversion process requires coordinated design and integration of electric machines, batteries, power converters, embedded controllers, protection systems, and vehicle interfaces. Ahmed’s published research includes work on predictive control for induction-motor drives.  [1].

Research Profile

Abdelsalam A. Ahmed is associated with the Electrical Power and Machines Engineering Department, Faculty of Engineering, Tanta University, Tanta, Egypt. Bibliographic records for his research identify work in electrical drives, model predictive control, induction-motor control, and related engineering applications [1][2]. His research profile is connected with the development and control of electrical-drive systems, with particular relevance to electric mobility, motor control, power electronics, and advanced control strategies.  [1].

Research Contributions

The recognized work contributes to the engineering development of EV conversion systems by focusing on the integration and validation of an embedded electric-drive architecture. Such systems require coordinated operation of the electric machine, drive electronics, embedded controller, energy source, and vehicle platform. Ahmed’s related publication on model predictive control demonstrates research experience in advanced control of induction-motor drives.  [1].

Publications

The supplied bibliometric record indicates 41 documents indexed under the specified Scopus author profile. The supplied profile also records 1,115 citations and an h-index of 13. A complete publication-level assessment would require examination of the individual Scopus records, including publication titles, abstracts, journals, co-authorship, citation relationships, and research topics. [1].

Research Impact

The supplied award information records 41 documents, 1,115 citations, and an h-index of 13. These values represent the bibliometric snapshot supplied for this award profile and should be understood as profile-level metrics that may change over time.His documented research on model predictive control contributes to the broader engineering literature on high-performance electrical drives. [1].

Award Recognition

Abdelsalam Ahmed is recognized with the Best Paper Award in Engineering for the research contribution represented by “Integration and Validation of an Embedded Electric Drive System for EV Conversion Kits: A Practical Industrial Case Study.”The award profile highlights the relevance of embedded electric-drive integration to vehicle electrification and EV conversion. Ahmed’s documented publication record also includes research on model predictive control and induction-motor drives, providing additional context for his work in electrical-drive engineering [1].

Conclusion

Abdelsalam Ahmed of the Faculty of Engineering, Tanta University, Egypt, is recognized with the Best Paper Award for research in Engineering. His recognized paper focuses on the integration and validation of an embedded electric-drive system for EV conversion-kit applications. His documented research includes electrical-drive control and model predictive control for induction-motor systems, while the supplied award profile identifies broader interests in electric vehicles, hybrid electric vehicles, power electronics, and energy-storage technologies.

External Links

References

  1. Ahmed, A. A., Koh, B. K., & Lee, Y. I. (2018).
    A comparison of finite control set and continuous control set model predictive control schemes for speed control of induction motors.
    IEEE Transactions on Industrial Informatics, 14(4), 1334–1346.
    DOI::https://doi.org/10.1109/TII.2017.2758393
  2. ORCID. (n.d.).
    ORCID record: Abdelsalam A. Ahmed.
    ORCID.https://orcid.org/0000-0002-0854-4411
  3. Elsevier. (n.d.).
    Scopus author details: Abdelsalam Ahmed, Author ID 56311161000.
    Scopus.https://www.scopus.com/authid/detail.uri?authorId=56311161000
  4. Best Paper Awards. (n.d.).
    International Research Excellence and Best Paper Awards.
    https://bestpaperawards.com/
  5. Seoul National University of Science and Technology. (n.d.).
    A comparison of finite control set and continuous control set model predictive control schemes for speed control of induction motors.
    Research Portal.
    https://pure.seoultech.ac.kr/en/publications/a-comparison-of-finite-control-set-and-continuous-control-set-mod/

Xingyu Zhou | Engineering | Best Researcher Award

Prof. Dr. Xingyu Zhou | Engineering | Best Researcher Award 

Assistant Professor | Beijing Institute of Technology | China

Dr. Zhou Xingyu, Assistant Professor at the Beijing Institute of Technology, is an accomplished researcher specializing in renewable energy and electric vehicles. He earned his Ph.D. in Vehicle Engineering from Chongqing University in 2020, following a Bachelor’s degree in Mechanical Design, Manufacturing, and Automation from the same institution. Dr. Zhou has extensive professional experience, including his current role as Assistant Professor at the School of Mechanical Engineering and Vehicle Engineering, Beijing Institute of Technology since March 2023, and a postdoctoral fellowship at the same institute from 2020 to 2023, where he contributed to the National Engineering Research Center for Electric Vehicles. His research interests focus on vehicle powertrain optimization, intelligent energy management, stochastic and data-driven modeling, and electric vehicle motion planning for enhanced energy efficiency. He has demonstrated expertise in multi-objective optimization, machine learning applications for powertrain design, and integration of fuel cell and hybrid electric vehicle systems. Dr. Zhou has led and participated in multiple high-impact research projects, including a National Natural Science Foundation of China Youth Project and key provincial and national projects on electric vehicle energy optimization and system integration. He has published 27 Scopus-indexed documents with 448 citations and an h-index of 11, in reputed journals such as Applied Energy, Journal of Power Sources, Journal of Cleaner Production, and IEEE Transactions on Vehicular Technology, serving frequently as corresponding author. His awards and honors include the Best Student Paper Award at the 2018 Italian Conference on Machines and Mechanisms. In addition, he contributes to the academic community as a reviewer for top journals and Guest Editor of Sustainability. Dr. Zhou Xingyu’s strong technical expertise, leadership in research projects, international collaborations, and commitment to sustainable innovation make him a highly deserving candidate for the Best Researcher Award, reflecting both outstanding academic achievements and meaningful contributions to advancing green mobility and energy-efficient transportation solutions globally.

Profiles: Scopus | ORCID

Featured Publications

Sun, C., Zhang, C., Sun, F., & Zhou, X. (2022). Stochastic co-optimization of speed planning and powertrain control with dynamic probabilistic constraints for safe and ecological driving. Applied Energy, 35, 119874.

Zhou, X., Sun, C., Sun, F., & Zhang, C. (2022). Commuting-pattern-oriented optimal sizing of electric vehicle powertrain based on stochastic optimization. Journal of Power Sources, 545, 23178.

Zhou, X., Sun, F., Zhang, C., & Sun, C. (2022). Stochastically predictive co-optimization of speed planning and powertrain controls for electric vehicles driving in random traffic environment safely and efficiently. Journal of Power Sources, 528, 231200.

Zhou, X., Sun, F., Sun, C., & Zhang, C. (2022). Predictive co-optimization of speed planning and powertrain energy management for electric vehicles driving in traffic scenarios: Combining strengths of simultaneous and hierarchical methods. Journal of Power Sources, 523, 230910.

Zhou, X., Sun, F., & Sun, C. (2021). Machine learning aided methods for reducing the dimensionality of the comprehensive energy economy optimization of fuel cell powertrains. Journal of Cleaner Production, 327, 129250.