Title: Real-time load spectrum analysis for lifetime prediction of e-mobility drivetrains

Authors: Michael Otto; Stefan Sendlbeck; Karsten Stahl

Addresses: Institute of Machine Elements, Gear Research Centre (FZG), Technical University of Munich (TUM), Munich, Germany ' Institute of Machine Elements, Gear Research Centre (FZG), Technical University of Munich (TUM), Munich, Germany ' Institute of Machine Elements, Gear Research Centre (FZG), Technical University of Munich (TUM), Munich, Germany

Abstract: The drivetrain is a critical subsystem in vehicles because any failure stops mobility and therefore current drivetrains are designed to be nearly fail-safe despite widely differing operating conditions and drivers of road vehicles. This applies especially to the main gearbox and is a special challenge for e-mobility, where weight reduction is mandatory. Optimisation may be possible by using vehicle-specific service intervals based on real driving loads. As a result, lighter gearboxes can be used, and a pre-damage warning and service is only required for demanding drivers or regular high load conditions. As a consecutive effect this may also allow lighter design of the rest of the drivetrain. Therefore, in this manuscript an innovative approach is presented to tackle this challenge by using a novel strategy of combining load spectrum calculation and condition monitoring that adjusts the lacking precision of lifetime prediction.

Keywords: transmission; load spectrum calculation; condition monitoring; e-mobility; gear; gearbox; load capacity.

DOI: 10.1504/IJPT.2023.134738

International Journal of Powertrains, 2023 Vol.12 No.3, pp.282 - 295

Received: 16 Nov 2021
Received in revised form: 07 Oct 2022
Accepted: 12 Oct 2022
Published online: 09 Nov 2023 *

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