Optimization of Car Use Time for Different Maintenance and Repair Scenarios Based on Life Cycle Assessment

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Abstract

New propulsion technologies and the development of electromobility increase the environmental efficiency of the transport sector. However, the current structure of car fleets with a large number of old cars with worse environmental parameters undermines the benefits of technological progress in the automotive industry. Older cars may require a more extensive service, involving a thorough overhaul, repair or even replacement of many parts. The result of using additional resources is a deterioration of environmental performance. This study considers various maintenance and repair scenarios and focuses on the use phase using the example of the popular Ford Focus passenger car model. The life cycle optimization model was used for environmental assessment, which determines the optimal duration of the car use phase, accounting for detailed service information and the type and environmental efficiency class of the different fuel versions. This model can be an effective tool for car fleet management and car replacement policy. Detailed life cycle inventories of 40 Ford Focus II diesel and petrol cars that represent all maintenance and repairs are the inputs to the life cycle optimization model. The inventory data were provided by the Ford Service Center in Szczecin (Poland), which regularly serviced the cars with a mileage of up to 200,000 km. Inventory at other stages of the cars’ life cycles was modeled using Ecoinvent data. The results show that by considering these vehicle servicing aspects on the basis of more detailed data, impact assessments are better represented compared to other studies. Depending on the replacement policy, the contribution of vehicle maintenance and repair can account for almost half of the cumulative life cycle burdens.

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APA

Danilecki, K., Smurawski, P., & Urbanowicz, K. (2023). Optimization of Car Use Time for Different Maintenance and Repair Scenarios Based on Life Cycle Assessment. Applied Sciences (Switzerland), 13(17). https://doi.org/10.3390/app13179843

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