TY - JOUR A1 - Gregor, Markus A1 - Bauder, Maximilian A1 - Kirsten Vidal de Oliveira, Aline A1 - Mast, Pascal A1 - Rüther, Ricardo A1 - Schweiger, Hans-Georg T1 - Approaches for Lifetime Prediction of Vehicle Traction Battery Systems During a Technical Inspection: A Systematic Review JF - World Electric Vehicle Journal N2 - Creating trust in society for new technologies, such as a new types of powertrains, and making them marketable requires transparent, neutral, and independent technical verification. This is crucial for the acceptance and success of electrified vehicles in the used car markets. A key component of electric vehicles is the traction battery, whose current and future condition, particularly regarding aging, determines its residual value and safe operation. This review aims to identify and evaluate methods for predicting the lifetime of onboard traction batteries, focusing on their applicability in technical inspections. A systematic literature and patent review was conducted using targeted keywords, yielding 22 patents and 633 publications. From these, 150 distinct lifetime prediction methods were extracted and categorized into a four-level mind map. These methods are summarized, cited, and structured in detailed tables. The relationships between approaches are explained to clarify the current research landscape. Long Short-Term Memory, Convolutional Neural Networks, and Particle Filters were identified as the most frequently used techniques. However, no methods were found suitable for predicting the lifetime of traction batteries during technical vehicle inspections, which operate under short test durations, limited data access, and diverse real-world operating conditions. Most studies focused on cell-level testing and did not address complete battery systems in operational vehicles. This gap highlights the need for applied research and the development of practical methods to support battery assessment in real-world conditions. Advancing this field is essential to foster confidence in battery systems and enable a sustainable transition to electromobility. UR - https://doi.org/10.3390/wevj17010003 Y1 - 2025 UR - https://doi.org/10.3390/wevj17010003 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-65631 SN - 2032-6653 VL - 17 IS - 1 PB - MDPI CY - Basel ER - TY - JOUR A1 - Walter, Gero A1 - Diel, Sergej A1 - Rufino Júnior, Carlos Antônio A1 - Schweiger, Hans-Georg A1 - Valente de Bessa, Iury A1 - Mallmann, Maíra A1 - Kirsten Vidal de Oliveira, Aline A1 - Odilio Dos Santos, Daniel A1 - Rüther, Ricardo T1 - Operating Behavior of a Photovoltaic-driven Electrolysis System JF - Revista Brasileira de Energia Solar UR - https://doi.org/10.59627/rbens.2024v15i1.456 Y1 - 2024 UR - https://doi.org/10.59627/rbens.2024v15i1.456 SN - 2526-2831 VL - 15 IS - 1 SP - 82 EP - 92 PB - ABENS CY - São Paulo ER -