Neha Bhushan, Saad Mekhilef, Kok Soon Tey, Mohamed Shaaban, Mehdi Seyedmahmoudian, Alex Stojcevski
In the original publication [...]
Emilia M. Szumska, Łukasz Pawlik, Damian Frej, Jacek Łukasz Wilk-Jakubowski
This literature review addresses a major research gap in electromobility by providing a comprehensive synthesis of machine learning (ML) and deep learning (DL) applications for forecasting energy consumption, managing battery state of charge (SoC), and integrating electric vehicl…
Maher Alaraj, Mohammed Radi, Elaf Alsisi, Munir Majdalawieh, Mohamed Darwish
The transport sector significantly contributes to global greenhouse gas emissions, making electromobility crucial in the race toward the United Nations Sustainable Development Goals. In recent years, the increasing competition among manufacturers, the development of cheaper batte…
Jingjin Bai, Jiujie Cai, Jiazheng Liu, Bailu Teng
Machine learning methods have gained significant attention in forecasting waterflooding performance in recent years, but their accuracy often remains insufficient for practical field applications. This study proposes a hybrid framework that integrates a linear dynamical system (L…
Stefania Conti, Giovanni Aiello, Salvatore Coco, Antonino Laudani, Santi Agatino Rizzo, Nunzio Salerno, et al.
The growing penetration of Electric Vehicles (EVs) in power distribution networks presents both challenges and opportunities for grid operators and planners. This paper provides a comprehensive review of recent advances in optimization techniques and machine learning (ML) approac…
The rapid growth of electric vehicles (EVs) has created an urgent need for sustainable end-of-life battery management systems. This paper presents a novel AI-driven framework for designing resilient reverse logistics networks that optimize the collection, testing, repurposing, an…
Alexander Winkler, Pranav Shah, Katrin Baumgärtner, Vasu Sharma, David Gordon, Jakob Andert
This study presents a novel state estimation approach integrating Deep Neural Networks (DNNs) into Moving Horizon Estimation (MHE). This is a shift from using traditional physics-based models within MHE towards data-driven techniques. Specifically, a Long Short-Term Memory (LSTM)…