Minimizing Emission for Timely Heavy-Duty Truck Transportation

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.

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Publication Details

Journal
IEEE Transactions on Intelligent Transportation Systems
Published
2024-12-16
DOI
https://doi.org/10.1109/tits.2024.3509899
Citations
2
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
0.41
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article

Minimizing Emission for Timely Heavy-Duty Truck Transportation

Wenjie Xu, Haibo Zeng, Runzhi Zhou, Junyan Su et al.
2 citations
IEEE Transactions on Intelligent Transportation Systems
Vehicle emissions and performance
0.41
article

Minimizing Emission for Timely Heavy-Duty Truck Transportation

Wenjie Xu, Haibo Zeng, Runzhi Zhou, Junyan Su, Minghua Chen, Qingyu Liu
article en
2 citations

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.

IEEE Transactions on Intelligent Transportation SystemsVol. 26(2)
City University of Hong Kong (HK), Peking University (CN), École Polytechnique Fédérale de Lausanne (CH), University of Pennsylvania (US), Virginia Tech (US)
Openalex Percentile: Top 38%
Vehicle emissions and performance
0.41
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