Test Methodology to Quantify and Analyze Energy Consumption of Connected and Automated Vehicles 2019-01-0116

A new generation of vehicle dynamics and powertrain control technologies are being developed to leverage information streams enabled via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity [1, 2, 3, 4, 5]. While algorithms that use these connected information streams to enable improvements in energy efficiency are being studied in detail, methodologies to quantify and analyze these improvements on a vehicle have not yet been explored fully. A procedure to test and accurately measure energy-consumption benefits of a connected and automated vehicle (CAV) is presented. The first part of the test methodology enables testing in a controlled environment. A traffic simulator is built to model traffic flow in Fort Worth, Texas with sufficient accuracy. The benefits of a traffic simulator are two-fold: (1) generation of repeatable traffic scenarios and (2) evaluation of the robustness of control algorithms by introducing disturbances. The traffic simulator is interfaced with a chassis dynamometer on which the real vehicle will be tested. Algorithms leverage information from the traffic simulator to produce control policies that are optimal in energy consumption. The control policy results in a specific speed of the “ego” vehicle. This speed is relayed back to the traffic simulator, which coordinates movement of the vehicles surrounding the ego vehicle. The second part of the test methodology analyzes energy consumption improvements enabled via CAV technologies. It is expected that the energy consumption reduction realized on a vehicle will differ from simulation studies that rely on simplified models. An advanced instrumentation and measurement scheme enables in-situ efficiency calculations across the powertrain by analyzing energy flows during transient operation of the vehicle. Preliminary results from vehicle testing on a chassis dynamometer are presented.