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Minimizing Emission for Timely Heavy-Duty Truck Transportation

  • Junyan Su
  • , Runzhi Zhou
  • , Qingyu Liu
  • , Wenjie Xu
  • , Minghua Chen*
  • , Haibo Zeng*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

We consider the problem of minimizing emission of a heavy-duty truck transporting freight between two locations subject to a hard deadline constraint. The truck is equipped with a multi-speed transmission and a modern combustion engine that intelligently switches among multiple fuel injection strategies at certain engine speeds (called switching speeds) to achieve lower emission profiles. Our objective is to minimize the emission by optimizing both path and speed planning for heavy-duty trucks with multi-speed transmission and multiple injection strategies in the engine. This emission minimization problem, while pervasive in practice, has two challenges: i) the emission rate function is discontinuous and non-convex due to switching of the fuel injections and gear ratios, which makes the common practice of driving at a constant speed on a road segment not eco-friendly; ii) the problem is NP-hard due to the combinatorial nature of the simultaneous path and speed planning. We tackle the first challenge by considering the case where the truck can travel at a heterogeneous speed profile over a road segment and then formulate the speed planning problem as a convex problem. We further identify special structures in this problem and provide an efficient method for computing the optimal speed profile. We then tackle the second challenge by developing an efficient heuristic for both path planning and speed planning to solve the emission minimization problem on the scale of national highway systems. Our extensive simulations on the US highway system show that our solution reduces up to 46% NOx emission as compared to the commonly-adopted fastest path approach. We also find that optimizing heterogeneous speed profiles reduce up to 32% emission as compared to their homogeneous counterpart, thus are necessary to be considered in eco-friendly truck operations. © 2024 IEEE.
Original languageEnglish
Pages (from-to)1454-1469
JournalIEEE Transactions on Intelligent Transportation Systems
Volume26
Issue number2
Online published16 Dec 2024
DOIs
Publication statusPublished - Feb 2025

Funding

This work was supported in part by the General Research Fund from Research Grants Council, Hong Kong, under Project 11206821; in part by the InnoHK Initiative, Government of the Hong Kong Special Administrative Region (HKSAR), Laboratory for Artificial intelligence (AI)-Powered Financial Technologies; and in part by Shenzhen-Hong KongMacau Science and Technology Project (Category C) under Project SGDX20220530111203026.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Research Keywords

  • emission
  • Energy-efficient transportation
  • engine fuel injection strategy
  • timely transportation

RGC Funding Information

  • RGC-funded

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