Mr. Paul Takyi-Aninakwa | Control Science and Engineering | Young Scientist Award
Ph.D., Southwest University of Science and Technology, China
Mr. Paul Takyi-Aninakwa is a recipient of the Young Scientist Award for his outstanding contributions to the field of Control Science and Engineering. He earned his Ph.D. from Southwest University of Science and Technology in China, where his research focused on innovative approaches to control systems. 🏆 With a dedication to pushing the boundaries of knowledge and a commitment to excellence, Mr. Takyi-Aninakwa has demonstrated remarkable expertise and promise in his field. His work showcases a blend of academic rigor and practical applications, positioning him as a rising star in the scientific community.
Profile
Research Interests
Diving into the forefront of technological innovation, the research of state-of-the-art lithium-ion batteries and their state parameter estimations for battery-powered devices and vehicles represents a critical frontier in sustainable energy solutions. 🔋 With a focus on enhancing efficiency and performance, this research delves into the intricate mechanics and materials that underpin friction, exploring areas such as sliding friction, supersonic sliding, and surface texturing. By unraveling the complexities of friction reduction, scientists aim to unlock new possibilities for improving the lifespan and functionality of battery-powered systems. This interdisciplinary approach promises to drive advancements in both energy storage and transportation sectors, shaping a greener future.
Education
Paul Takyi-Aninakwa’s academic journey spans continents, reflecting a pursuit of excellence in engineering across diverse landscapes. 🎓 He earned his Ph.D. in Control Science and Engineering from Southwest University of Science and Technology in Mianyang, Sichuan Province, China. During this time, he contributed to the New Energy Measurement and Control Laboratory within the School of Information Engineering. Prior to his doctoral studies, he completed his MSc in Mechanical Engineering at the same university, further enriching his expertise. 📚 Before venturing abroad, he obtained his B.Sc. in Mechanical Engineering from Kwame Nkrumah University of Science and Technology in Kumasi, Ashanti Region, Ghana, laying the foundation for his future achievements.
Work Experience
Paul Takyi-Aninakwa’s professional journey intertwines a blend of academic pursuits and practical experiences across continents, reflecting his multifaceted expertise and dedication to innovation. 🌍 As a research and innovation team member and African Community Team Leader at the Co-creation and Innovation Center of Southwest University of Science and Technology in China, he spearheads collaborative initiatives driving technological advancements. Previously, he served as Operations/Maintenance Manager at Logistics Masters Limited in Takoradi, Ghana, overseeing the rental and hiring of heavy-duty equipment for construction projects. His tenure at Japan Motors Trading Company Limited and Ghana Highway Authority further honed his skills in mechanical and maintenance operations, showcasing a diverse skill set poised for impactful contributions.
Research Direction
Paul Takyi-Aninakwa’s academic trajectory reflects a journey marked by rigorous exploration and innovation in engineering disciplines. 📚 As a doctoral student at the New Energy Measurement and Control Laboratory within the School of Information Engineering at Southwest University of Science and Technology in China, his research is dedicated to pioneering new methods for energy measurement and control, specifically targeting the development of efficient battery management systems for lithium-ion batteries in electro-mobility. 🚗 His master’s studies delved into the realm of supersonic sliding friction, utilizing advanced numerical software to simulate and analyze friction phenomena, culminating in the proposal of novel surface texture topographies for friction reduction. 🔄 During his undergraduate tenure at Kwame Nkrumah University of Science and Technology in Ghana, he cultivated a solid foundation in mechanical engineering principles, laying the groundwork for his future innovations.
Publications Top Notes
Title: An optimized long short-term memory-weighted fading extended Kalman filtering model with wide temperature adaptation for the state of charge estimation of lithium-ion batteries. Year: 2022 Link: Applied Energy 326 (2022) 120043 Authors: Paul Takyi-Aninakwa, Shunli Wang*, Hongying Zhang, Carlos Fernandez, Xiaoyong Yang
Title: An optimized relevant long short-term memory-squared gain extended Kalman filter for the state of charge estimation of lithium-ion batteries. Year: 2022 Link: Energy 260 (2022) 125093 Authors: Paul Takyi-Aninakwa, Shunli Wang*, Hongying Zhang, Huan Li, Wenhua Xu, Carlos Fernandez
Title: A hybrid probabilistic correction model for the state of charge estimation of lithium-ion batteries considering dynamic currents and temperatures. Year: 2023 Link: Energy 273 (2023) 127231 Authors: Paul Takyi-Aninakwa*, Shunli Wang, Hongying Zhang, Yang Xiao, Carlos Fernandez
Title: An enhanced lithium-ion battery state-of-charge estimation method using long short-term memory with an adaptive state update filter incorporating battery parameters. Year: 2024 Link: Engineering Applications of Artificial Intelligence 132 (2024) 107946 Authors: Paul Takyi-Aninakwa*, Shunli Wang, Hongying Zhang, Alhamdu Nuhu Bage, Faisal Masahudu, Josep M. Guerrero
Title: Enhanced multi-state estimation methods for lithium-ion batteries considering temperature uncertainties. Year: 2023 Link: Journal of Energy Storage 66 (2023) 107495 Authors: Paul Takyi-Aninakwa*, Shunli Wang, Hongying Zhang, Yang Xiao, Carlos Fernandez
Title: A NARX network optimized with an adaptive weighted square-root cubature Kalman filter for the dynamic state of charge estimation of lithium-ion batteries. Year: 2023 Link: Journal of Energy Storage 68 (2023) 107728 Authors: Paul Takyi-Aninakwa*, Shunli Wang, Hongying Zhang, Yang Xiao, Carlos Fernandez
Title: An ASTSEKF optimizer with nonlinear condition adaptability for the state of charge estimation of lithium-ion batteries. Year: 2023 Link: Journal of Energy Storage 70 (2023) 108098 Authors: Paul Takyi-Aninakwa*, Shunli Wang, Hongying Zhang, Yang Xiao, Carlos Fernandez