Vehicle optimization based on customer usage

Purpose and goal

Lifetime Requirements are crucial for the design of trucks. Variation in life is strongly linked to variation in use and to understand customers´ cycle is a prerequisite for energy and transport optimization. In this project, we modeled events with Markov chain. We have used the Hidden Markov Models to identify and cornering and maneuvers based on CAN data. We have worked with an Off-line and On-line algorithm. In several projects, we have described / differentiate customer use in several classes, leading to more optimized components.

Expected results and effects

The project has been let to a better understanding of how we are but statistical models to understand / modeling how customers use our vehicles. By rate environment, we can classify our components. Optimized components leads to less overall weight of the vehicle and greater cargo capacity. This leads to less energy consumption in production and a relatively lower fuel consumption

Planned approach and implementation

The main scientific work has been done by a graduate student in Mathematical Statistics at Chalmers. The work has been published in the five articles. The PhD student has taken the Licentiate degree and a doctoral degree. We have had a number of supervisors from Chalmers and SP. The results have been gradually implemented in Volvo´s requirements management and later in a number of products / components.