Design and assessment of an eco--driving PMP algorithm for optimal deceleration and gear shifting in trucks

TL;DR

This paper presents an eco-driving algorithm for trucks using PMP to optimize deceleration and gear shifting, reducing fuel consumption while enabling real-time, driver-in-the-loop assistance.

Contribution

It introduces a PMP-based eco-driving strategy for trucks that is computationally efficient and suitable for real-time implementation, incorporating driver feedback.

Findings

Significant fuel savings achieved in simulations.

Optimization is computationally inexpensive for real-time use.

Strategy adapts to velocity changes and driver feedback.

Abstract

In this paper, an eco--driving Pontryagin maximum principle (PMP) algorithm is designed for optimal deceleration and gear shifting in trucks based on switching among a finite set of driving modes. The PMP algorithm is implemented and assessed in the IPG TruckMaker traffic simulator as an eco--driving assistance system (EDAS). The developed EDAS strategy reduces fuel consumption with an optimized velocity profile and, in practice, allows contextual feedback incorporation from the driver for safety. Furthermore, the optimization over driving modes is computationally inexpensive, allowing the methodology to be used online, in real--time. Simulation results show that significant fuel savings can be achieved proportional to the number of velocity events and the difference between current velocity and final desired velocity for each event.