Chaozhe R. He

Fuel Consumption Optimization of Heavy-Duty Vehicles with Grade, Wind, and Traffic Information

In this paper, we establish a mathematical framework that allows us to optimize the speed profile and select the optimal gears for heavy-duty vehicles (HDVs) traveling on highways while varying parameters. The key idea is to solve the analogous boundary value problem (BVP) analytically for a simple scenario (linear damped system with quadratic elevation profile) and use this result to initialize a numerical continuation algorithm. Then, the numerical algorithm is used to investigate how the optimal solution changes with parameters. In particular, we gradually introduce nonlinearities (air resistance and engine saturation), implement different elevation profiles, and incorporate external perturbations (headwind and traffic). This approach enables real-time optimization in dynamic traffic conditions, therefore may be implemented on-board. [DOI: 10.1115/1.4033895]

Sequential parametric optimization for connected cruise control with application to fuel economy optimization

In this paper, we present a framework for connected cruise control (CCC) design utilizing wireless vehicle-to-vehicle (V2V) communication. We propose a sequential optimization approach to select the control parameters for the available communication links that allows graceful degradation of performance when certain links become unavailable. We apply the theoretical results to improve the fuel economy of a heavy duty vehicle while requiring head-to-tail string stability of the vehicle string. Simulation results are presented to demonstrate the effectiveness of the proposed controller in improving fuel economy.

Saving fuel using wireless vehicle-to-vehicle communication

In this paper, we compare two different connected cruise control strategies that utilize vehicle-to-vehicle (V2V) communication to monitor multiple vehicles ahead in order to save fuel. One strategy uses direct feedback while the other is based on dynamic optimization that assigns the control action in a receding horizon fashion while relying on preview information about the vehicle immediately ahead. We demonstrate that both methods produce significant fuel improvements but the performance of the second controller depends significantly on the length of time horizon as well as the accuracy of the preview information.

Fuel Consumption Optimization of Heavy-Duty Vehicles: An Analytical Approach

In this paper, we establish a mathematical framework that allows us to optimize the speed profile and select the optimal gears for heavy-duty vehicles. The key idea is to solve the analogous boundary value problem analytically for a simple scenario (linear damped system with quadratic elevation profile) and use this result to initialize a numerical continuation algorithm. Then the numerical algorithm can be used to gradually introduce nonlinearities (air resistance, engine saturation), implement data-based elevation profiles, and incorporate external perturbations (wind, traffic). This approach enables real-time optimization in dynamic traffic conditions, therefore may be implemented on board.Copyright

Optimal Gear Shift Schedule Design for Automated Vehicles: Hybrid System Based Analytical Approach

In this paper, we present a systematic design framework for gear shift schedule using hybrid system theory primarily intended for automated vehicles. The longitudinal motion of the vehicle is regulated by a PI controller that determines the required axle torque. The longitudinal dynamics of the vehicle with a gear box is modeled as a hybrid system, and an optimization-based gear shift schedule design is introduced. This guarantees that the propulsion requirements are delivered while minimizing fuel consumption. The resulting dynamics is proven to be stable in the presence of constraints. We apply our framework to heavy-duty vehicle gear shift schedule design and evaluate the performance of the controller using numerical simulations.

Hybrid system based analytical approach for optimal gear shifting schedule design

In this paper, we present a systematic design for gear shifting using a hybrid system approach. The longitudinal motion of the vehicle is regulated by a PI-controller that determines the required axle torque. The gear scheduling problem is modeled as a hybrid system and an optimization-based gear shifting strategy is introduced, which guarantees that the propulsion requirements are delivered while minimizing fuel consumption. The resulting dynamics is proved to be stable theoretically. In a case study, we compare our strategy with a standard approach used in the industry and demonstrate the advantages of our design for class 8 trucks.Copyright