Automotive companies are looking to use vehicle data for increasingly important applications such as real-world emissions, fuel economy and driving patterns, and prognostics. Working with this big engineering data requires systems that can handle the sheer volume, variety, and velocity of that data. These systems must include flexible, scalable algorithms deployed in a production environment so engineers can derive insights from the data.

Read this white paper to learn about a research project to implement a vehicle fleet test data analytics system. The team used MATLAB® to extract key insights for improving engine and vehicle design, including:

  • Understanding real-world brake-specific fuel consumption
  • Identifying problematic traffic patterns in which fleet vehicles are consuming the most fuel
  • Run closed-loop system simulation by connecting your PID Controller block to the plant model
  • Visualizing, optimizing, and analyzing vehicle fleet performance characteristics with MATLAB and Hadoop

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