Harmonizing Heterogeneous Diagnostic Data of a Vehicle Fleet for Data-Driven Analytics

Data-driven technologies, such as predictive maintenance, become increasingly important to today's automotive industry due to advancements of connected cars and Over-the-Air technologies. A data source that has barely been used in the literature so far is diagnostic data, which is obtained by sending requests to the electronic control units of a vehicle. Diagnostic data can be collected cost-effectively and is already available on a large scale to car manufacturers today. However, the use of diagnostic data is associated with some difficulties. The set of measured variables differs greatly between different vehicles of the same type due to different configurations and therefore differences in the electronic control units. In this contribution, we show how diagnostic data can be harmonized for the use of data-driven modeling. An heuristic three-step procedure is introduced to identify similar measured variables. Finally, our approach is verified on a synthetic data set. Future data-driven technologies are able to use larger and more cost-efficient data sets this way.

[1]  Juan Mora,et al.  An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov-Smirnov two-sample test , 2015, Expert Syst. Appl..

[2]  Armin Zimmermann,et al.  Flexible On-Board Stream Processing for Automotive Sensor Data , 2010, IEEE Transactions on Industrial Informatics.

[3]  Slawomir Nowaczyk,et al.  Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data , 2015, Eng. Appl. Artif. Intell..

[4]  N. Nagelkerke,et al.  A note on a general definition of the coefficient of determination , 1991 .

[5]  S. Nash,et al.  Linear and Nonlinear Optimization , 2008 .

[6]  Hinrich Schütze,et al.  Introduction to information retrieval , 2008 .

[7]  Ahmed K. Elmagarmid,et al.  Duplicate Record Detection: A Survey , 2007, IEEE Transactions on Knowledge and Data Engineering.

[8]  Reinhard German,et al.  Routing of Safety-Relevant Messages in Automotive ECU Networks , 2009, 2009 IEEE 70th Vehicular Technology Conference Fall.

[9]  Jean D. Gibbons,et al.  Kolmogorov-Smirnov Two-Sample Tests , 1981 .

[10]  Ken Kennedy,et al.  Automotive big data: Applications, workloads and infrastructures , 2015, 2015 IEEE International Conference on Big Data (Big Data).

[11]  Shin Ishii,et al.  Expanding histogram of colors with gridding to improve tracking accuracy , 2015, 2015 14th IAPR International Conference on Machine Vision Applications (MVA).

[12]  M. Barthelemy,et al.  Human mobility: Models and applications , 2017, 1710.00004.

[13]  Erik Frisk,et al.  Treatment of accumulative variables in data-driven prognostics of lead-acid batteries , 2015 .

[14]  Mark Last,et al.  Predictive Maintenance with Multi-target Classification Models , 2010, ACIIDS.