Eco-Routing of Plug-In Hybrid Electric Vehicles in Transportation Networks

Houshmand, Arian; Cassandras, Christos G.

doi:10.1109/itsc.2018.8569982

Cited by 14 publications

(6 citation statements)

References 23 publications

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“…Optimal EMS [26,27] aimed at minimizing fuel consumption for a given battery consumption is obtained for a prescribed speed profile using the Pontryagin's minimum principle (PMP), which can be rather time consuming. In an attempt to reduce the computational load of the EMS, approximated optimization methods leverage the simple form of the predicted power demand at route planning level [28], or make use of historical information about average power split on recorded driving cycles [29,30]. In this work, we extend the findings presented in [28] to define a fast numerical solution of the EMS for HEVs by predicting travel speed with a simple deterministic profile.…”

Section: Related Workmentioning

confidence: 98%

A general constrained optimization framework for the eco-routing problem: Comparison and analysis of solution strategies for hybrid electric vehicles

Nunzio

Gharbia

Sciarretta

2021

Transportation Research Part C: Emerging Technologies

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Vehicles electrification marks a very important step towards sustainable mobility. However, energy efficiency and driving range of electrified vehicles are nowadays a major concern. From an algorithmic perspective, eco-routing opens up new possibilities regarding the strategies and tools aimed at improving energy efficiency by finding an energy-minimal route under different constraints coming from vehicle characteristics (powertrain, battery capacity, etc.) and user preferences (travel time, etc.). In this work, a powertrain-independent speed prediction model is presented. This model is then used to derive a fast numerical solution of the powertrain energy management for hybrid electric vehicles. Furthermore, a new general formulation is derived for the minimum-energy navigation problem, with a focus on the specific complexity introduced by electrified vehicles. The general constrained optimization problem is reformulated in several alternative ways in order to achieve a solution in limited computation time. The most commonly used approaches nowadays in the literature (integer programming and shortest path algorithms on directed graphs) are compared and benchmarked in terms of solution accuracy and computational effort. The objective is to identify best-practices in accurately and efficiently solving the constrained eco-routing problem.

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Section: Related Workmentioning

confidence: 98%

A general constrained optimization framework for the eco-routing problem: Comparison and analysis of solution strategies for hybrid electric vehicles

Nunzio

Gharbia

Sciarretta

2021

Transportation Research Part C: Emerging Technologies

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“…Moreover, the traveling time of commuting through the fastest route decreases as we inject more CAVs to the system. Typically, we expect a trade off between time saving and energy saving in routing problems [24], [25]. However, in Fig.…”

Section: A Braess Network Examplementioning

confidence: 98%

“…In order to solve the eco-routing problem for CAVs, we follow the same formulation used in [25]. The essence of this eco-routing model is that it categorizes each link based on its average speed into 3 different modes: heavy traffic, medium traffic, and low traffic links (note that we can have more than 3 modes as well).…”

Section: B Eco-routing Problem Formulation For Phevsmentioning

confidence: 99%

The Penetration Rate Effect of Connected and Automated Vehicles in Mixed Traffic Routing

Houshmand

Wollenstein-Betech

Cassandras

2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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We study the problem of routing Connected and Automated Vehicles (CAVs) in the presence of mixed traffic (coexistence of regular vehicles and CAVs). In this setting, we assume that all CAVs belong to the same fleet, and can be routed using a centralized controller. The routing objective is to minimize a given overall fleet traveling cost (travel time or energy consumption). We assume that regular vehicles (non-CAVs) choose their routing decisions selfishly to minimize their traveling time. We propose an algorithm that deals with the routing interaction between CAVs and regular uncontrolled vehicles. We investigate the effect of assigning system-centric routes under different penetration rates (fractions) of CAVs. To validate our method, we apply the proposed routing algorithms to the Braess Network and to a sub-network of the Eastern Massachusetts (EMA) transportation network using actual traffic data provided by the Boston Region Metropolitan Planning Organization. The results suggest that collaborative routing decisions of CAVs improve not only the cost of CAVs, but also that of the non-CAVs. Furthermore, even a small CAV penetration rate can ease congestion for the entire network.

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“…Houshmand, et al [11] a CRPTC a "combined routing and a power train control algorithm" to parallely estimate the power consumption and the possible route with the minimum energy consumption is proposed in the paper to provide an eco-routing for the electric vehicles to save energy and the time.…”

Section: Related Workmentioning

confidence: 99%

A Dynamic Routing Model for Hybrid Electric Vehicles

Dr¹

2019

JEEA

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The recent steady hikes in the prices of the oil/gases and the need for the healthier ecosystem, has led to the larger increase in the interest of the vehicles to move to alternative energy resources that causes a low carbon emission. The hybrid electric vehicle that utilizes both the internal combustion engine and the electrical engine is becoming a predominant option for the vehicle with the low carbon emission than the pure electric vehicle that is restricted due to the limited battery usage. To have an optimal mode of selection of the routes for the hybrid electric vehicle, the paper proposes a method for the identification of minimum delay geographical routing in advance by determining the shortest paths available to the destinations using the prim’s minimum spanning tree algorithm, and employing Tabu-Search in enumerating the minimum delay path in order to have a reduced energy usage and a low carbon emission that paves way for the development of the eco-friendly environment.

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Eco-Routing of Plug-In Hybrid Electric Vehicles in Transportation Networks

Cited by 14 publications

References 23 publications

A general constrained optimization framework for the eco-routing problem: Comparison and analysis of solution strategies for hybrid electric vehicles

A general constrained optimization framework for the eco-routing problem: Comparison and analysis of solution strategies for hybrid electric vehicles

The Penetration Rate Effect of Connected and Automated Vehicles in Mixed Traffic Routing

A Dynamic Routing Model for Hybrid Electric Vehicles

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