Improving behavior of automotive systems with collected runtime data visualization

In order to improve "trial-and-error" approach normally used to optimize the performance of automotive systems, we describe here a data acquisition system that simultaneously takes into account multiple variables. The solution is to collect data from different sources into computing system, convert them into measureable values and present the information through the human understandable system. Behavior and usage of the automotive system can be improved by observing concurently different information using the visualization results in a process of understanding and upgrading. When presented in intuitive way, the results showed many improvement possibilities not only on the automotive system itself but also on the driving techniques of the driver. Additionally, the visualization approach reduces the number of iterations and testings as there is possibility to measure and compare the behavior after adequate values are changed. During the research, based on hardware limitations, the sampling rate of 5 Hz has been implemented and tested which opened a completely new view on the behavior of the automotive systems.