This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 101–107 of 107 papers
Junze Yin
This paper analyzes BYD's competitive strategies under green transition. Vertical integration (75% core component self-sufficiency) and high R&D spending (6.6% of revenue) drove a 21.9% global NEV market share in 2023, but a 78% debt ratio …
Hakan İnal, Emma Karlsson, Oliver Nåfors +2
This study compares the life cycle cost (LCC) of BEV, PHEV, and ICEV in Sweden in 2024. The Tesla Model Y (BEV) has an LCC of 877,736 SEK, the Volkswagen T-Roc (ICEV) the lowest at 635,222 SEK, and the Volvo XC60 (PHEV) the highest at 1,104…
Shift2Zero Partners
This deliverable documents user-centered requirements elicitation for Shift2Zero innovations, collecting data from 87 interviews, 8 workshops, a survey of 512 participants, and simulations. It defines 181 technical requirements for electric…
Guo-Ying Han, Zonglin Li
This review systematically structures EV sales research from 2016-2025, selecting 194 papers from 1518 records. It develops a macro-meso-micro framework for determinants and finds econometric models dominant (54%) but machine learning (18%)…
Sai Luo, Kaihang Zhang, Guangwei Li +4
This paper reviews the current status of fuel cell electric vehicle (FCEV) industrialization in China and discusses future prospects. It outlines policy support, technological progress, and infrastructure development, while identifying chal…
Raghavendra Kurva
This technical review examines AI and machine learning approaches for real-time carbon footprint monitoring of electric vehicles (EVs). By integrating data from sensors, vehicle systems, and recycling facilities, dynamic emission profiles a…
Gayathri Asokan, Rajkumar Raju cEng, Chandan Dhananjaya +1
This paper proposes a technical framework for life cycle assessment (LCA) specifically for EV battery recycling. It identifies mining and manufacturing as carbon hotspots, and shows that end-of-life strategies like hydrometallurgical recycl…
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