Joint Component Sizing and Energy Management for Fuel Cell Hybrid Electric Trucks

Xun, Qian; Murgovski, Nikolce; Liu, Yujing

doi:10.1109/tvt.2022.3154146

Cited by 19 publications

(5 citation statements)

References 52 publications

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“…For a route with variable gradient profiles, the optimal driving strategies might be changed, since the battery system has not the ability to provide enough energy for traction system and auxiliary system using a min-time strategy. In this setting, the outer loop of the bi-level optimization algorithm is active, which is responsible for searching an optimal value 𝜆 * e to satisfy the constraint (29).…”

Section: Optimal Results On a Route With Gradient Variablementioning

confidence: 99%

“…A cell can be described by an equivalent circuit, namely an internal voltage source u cell in series with a constant internal resistance R cell [29]. The open circuit voltage (OCV) u cell of the battery can be approximated as a constant value.…”

Section: System Modellingmentioning

confidence: 99%

“…In consistent with the demanded power of train operations, multiple cells of battery should be connected in parallel and series, shown in Figure 2, and n ess = n s n p , where n ess , n s and n p are total number of cells in the pack, number of cells connected in series in a string and number of strings connected in parallel, respectively. A cell can be described by an equivalent circuit, namely an internal voltage source u cell in series with a constant internal resistance R cell [29]. The open circuit voltage (OCV) u cell of the battery can be approximated as a constant value.…”

Section: Energy Storage System Modelmentioning

confidence: 99%

See 2 more Smart Citations

Optimal driving strategies for emergency operation of high‐speed trains using on‐board energy storage systems

Zhu

Zhang

Chen

et al. 2023

IET Intelligent Trans Sys

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A power outage occurs when there is an interruption to traction power system. In such emergency situations, trains are expected to achieve autonomy operation powered by on‐board energy storage systems (OESS). This paper presents optimization models and methods to find optimal driving strategies for train emergency operation. Specifically, a nonlinear and non‐convex program is first formulated in space‐domain to minimize trip time under the limits of power and energy capacity of OESS. To improve computational efficiency, the time dynamics is removed from constraints and adjoined to the cost function. Furthermore, convex modelling steps are proposed to reformulate the problem as a convex program that can be solved efficiently. A bi‐level algorithm is designed to obtain optimal driving strategies that can arrive at destinations as soon as possible. Compared to energy‐optimal driving strategies, the proposed methods can effectively reduce the trip time.

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Section: Optimal Results On a Route With Gradient Variablementioning

confidence: 99%

Section: System Modellingmentioning

confidence: 99%

Section: Energy Storage System Modelmentioning

confidence: 99%

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Optimal driving strategies for emergency operation of high‐speed trains using on‐board energy storage systems

Zhu

Zhang

Chen

et al. 2023

IET Intelligent Trans Sys

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“…In the power system of a hydrogen-electric hybrid vehicle, an effective energy management strategy (EMS) must be developed based on the overall power requirements of FCV to improve the entire performance of the vehicle. 5 , 6 …”

Section: Introductionmentioning

confidence: 99%

A real-time energy management strategy for fuel cell vehicle based on Pontryagin’s minimum principle

Quan,

Guo,

et al. 2024

iScience

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“…F UEL cell electric vehicles (FCEVs), utilizing hydrogen instead of diesel and gasoline as power fuels, are a kind of clean energy vehicles with the advantages of high-energy conversion efficiency, low noise, and zero exhaust emissions [1], [2], [3]. Because FCEVs are necessary equipped with an auxiliary energy source to realize the power demand for transient peak and recovery of braking energy, the energy management strategy (EMS) is indispensable [4], [5]. However, highly nonlinear system on different timescales, uncertainty in driving conditions and heavy computational load pose major obstacles in EMS design [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Energy Management Strategy of a Fuel Cell Electric Vehicle With Global Optimal Learning

Hou

Yin

Plá³

et al. 2023

IEEE Trans. Transp. Electrific.

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This article proposes a novel energy management strategy (EMS) for a fuel cell electric vehicle (FCEV). The strategy combines the offline optimization and online algorithms to guarantee optimal control, real-time performance, and better robustness in an unknown route. In particular, dynamic programming (DP) is applied in a database with multiple driving cycles to extract the theoretically optimal power split between the battery and fuel cell with a priori knowledge of the driving conditions. The analysis of the obtained results is then used to extract the rules to embed them in a real-time capable fuzzy controller. In this sense, at the expense of certain calibration effort in the offline phase with the DP results, the proposed strategy allows on-board applicability with suboptimal results. The proposed strategy has been tested in several actual driving cycles, and the results show energy savings between 8.48% and 10.71% in comparison to rule-based strategy and energy penalties between 1.04% and 3.37% when compared with the theoretical optimum obtained by DP. In addition, a sensitivity analysis shows that the proposed strategy can be adapted to different vehicle configurations. As the battery capacity increases, the performance can be further improved by 0.15% and 1.66% in conservative and aggressive driving styles, respectively.

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Joint Component Sizing and Energy Management for Fuel Cell Hybrid Electric Trucks

Cited by 19 publications

References 52 publications

Optimal driving strategies for emergency operation of high‐speed trains using on‐board energy storage systems

Optimal driving strategies for emergency operation of high‐speed trains using on‐board energy storage systems

A real-time energy management strategy for fuel cell vehicle based on Pontryagin’s minimum principle

Real-Time Energy Management Strategy of a Fuel Cell Electric Vehicle With Global Optimal Learning

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