%0 Thesis %A Ibitayo, Ifeoluwa Jimmy %D 2019 %T Enhanced Class 8 Truck Platooning via Simultaneous Shifting and Model Predictive Control %U https://hammer.purdue.edu/articles/thesis/Enhanced_Class_8_Truck_Platooning_via_Simultaneous_Shifting_and_Model_Predictive_Control/8280956 %R 10.25394/PGS.8280956.v1 %2 https://hammer.purdue.edu/ndownloader/files/15483041 %K class 8 trucks %K platooning %K fuel savings %K simulation %K shifting %K model predictive control %K Automation and Control Engineering %K Autonomous Vehicles %K Control Systems, Robotics and Automation %X
Class 8 trucks on average drive the most miles and consume the most fuel of any major vehicle category annually. Indiana specifically is the fifth busiest state for commercial freight traffic and moves $750 billion dollars of freight annually, and this number is expected to grow by 60% by 2040. Reducing fuel consumption for class 8 trucks would have a significant benefit on business and the proportional decrease in CO2 would be exceptionally beneficial for the environment.

Platooning is one of the most important strategies for increasing class 8 truck fuel savings. Platooning alone can help trucks save upwards of 7% platoon average fuel savings on flat ground. However, it can be difficult for a platooning controller to maintain a desired truck separation during uncoordinated shifting events. Using a high-fidelity simulation model, it is shown that simultaneous shifting–having the follow truck shift whenever the lead truck shifts (unless shifting would cause its engine to overspeed or underspeed)–decreases maximum truck separation by 24% on a moderately challenging grade route and 40% on a heavy grade route.

Model Predictive Control (MPC) of the follow truck is considered as a means to reduce the distance the follow truck falls behind during uncoordinated shifting events. The result in simulation is a reduction in maximum truck separation of 1% on a moderately challenging grade route and 19% on a heavy grade route. However, simultaneous shifting largely alleviates the need for MPC for the sake of tracking for the follow truck.

A different MPC formulation is considered to dynamically change the desired set point for truck separation for routes through a strategy called Route Optimized Gap Growth (ROGG). The result in simulation is 1% greater fuel savings on a moderately challenging grade route and 7% greater fuel savings on a route with heavy grade for the follow truck.
%I Purdue University Graduate School