Multivariate Simulation of Product Fleets based on Usage Data: Case Study on Light Electric Vehicles

As the requirements for technically complex products and their functionality increase, product complexity continues to rise.At the same time, development times and costs must be reduced to ensure that technical products remain marketable.This leads to an increase in possible damage causalities and potential field failures.This applies in particular to the development of new markets, such as electromobility in the light vehicle sector, known as light electric vehicles (LEVs).The battery systems installed in these vehicles harbor a comparatively high risk of functionand safety-critical failures.These present companies with new challenges when operating product fleets in the private and commercial sectors due to the high level of safety and reliability required.To reduce the risk and increase the reliability of LEVs in the field, analysing product data from the field is highly relevant in order to be able to predict the remaining useful life.One way of supporting the reliability analysis process during the utilisation phase of the product life cycle is to simulate and prognose the further use of a product or a product fleet.The existing and simulated usage data can then be used for forecasts regarding the remaining useful life of products.This paper presents the results of a feasibility study in which a concept for the multivariate simulation of product fleets based on usage data from the field is applied in the context of LEVs.Field data from a Kumpan electric 54 e-moped, which was recorded over a period of several days, serves as the data basis.The available data was analysed and used for the multivariate simulation.Finally, the simulation results were compared with the original data and a conclusion was drawn.