Design and Validation of Energy Management Strategy for Extended-Range Fuel Cell Electric Vehicle Using Bond Graph Method

Song, Ke; Wang, Yimin; An, Cancan; Xu, Hongjie; Ding, Yuhang

doi:10.3390/en14020380

Cited by 11 publications

(7 citation statements)

References 52 publications

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“…where fc  represents the efficiency. Combining the empirical formula for polarization voltage mentioned above and the fundamental principles for constructing BG [23], the BGM for the FC is depicted in Figure 3. The curve depicting the relationship between "Current " and "Voltage" is illustrated in Figure 4.…”

Section: ) Fuel Cell Modelmentioning

confidence: 99%

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Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming

Li,

Liu,

Wang

et al. 2024

IEEE Access

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In addressing challenges associated with the constrained enhancement of range performance in pure electric tractors, the difficulty in achieving genuinely eco-friendly agricultural machinery with hybrid powertrains, and the outdated approaches to energy optimization in hydrogen fuel cell tractors, a comprehensive methodology covering the entire spectrum of system design, optimization, and validation is presented. This method constructs an integrated electromechanical and hydraulic power bond graph model for an agricultural tractor, encompassing energy systems, drive systems, and lifting systems. It achieves rapid interaction between 20-sim software and Matlab/Simulink software through a script toolbox. In order to tackle the real-time applicability challenges of dynamic programming, a hierarchical dynamic programming is proposed. The dynamic programming strategy results serve as the upper-level output. At the lower layer, preprocessing of impact value variables is carried out to filter the input variables for the general regression neural network. This enables the real-time application of the dynamic programming algorithm and significantly reduces training time. Finally, a Matlab-HIL test platform is established, utilizing 20-sim, Matlab/Simulink, HIL cabinet, and PowerECU-57A controller as the core components for the test of modelin-the-loop and hardware-in-the-loop. The results demonstrate the correctness and superiority of the designed tractor simulation model and energy management strategy model compared to the power-following strategy. Specifically, in plowing conditions, the dynamic programming and hierarchical dynamic programming strategies exhibited reductions of 10.278% and 6.728%, respectively, in equivalent hydrogen consumption compared to power-following strategy. In transportation conditions, the reductions are 16.02% for dynamic programming strategy and 4.87% for hierarchical dynamic programming strategy, both relative to powerfollowing strategy. This study lays the theoretical groundwork for modeling dynamic systems of tractors and optimizing energy management.INDEX TERMS hydrogen fuel cell tractors, bond graph, energy management strategy, model-in-the-loop, hard-ware-in-the-loop.

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Section: ) Fuel Cell Modelmentioning

confidence: 99%

“…The battery model described in this paper uses a first-order RC model, and the equivalent circuit is shown in Figure 6 [24]. The relevant parameters are listed in According to the equivalent circuit, the output current of the lithium battery is as follows:…”

Section: ) Battery Modelmentioning

confidence: 99%

Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming

Li,

Liu,

Wang

et al. 2024

IEEE Access

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“…Furthermore, to assess the performance of the constructed model, comparative experiments are conducted between the proposed algorithm and the model algorithm proposed by the priority graph method [29], AHP, entropy method [30], and Zhu et al (2022). The experiments are conducted by evaluating accuracy and error of factor classification.…”

Section: Experimental Evaluationmentioning

confidence: 99%

Fuzzy comprehensive evaluation and quantitative weight analysis in structure management of human resources

Zhang

2023

PLoS ONE

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This research delves into the application effects of Fuzzy Comprehensive Evaluation (FCE) and quantitative weight analysis in the structure management of human resources (SMHR) to optimize the structure management. The research begins by analyzing the existing problems in SMHR, such as incomplete performance feedback and error-prone outsourcing decisions. By leveraging human resource management (HRM) characteristics, the researchers construct the SMHR evaluation index system. The Analytical Hierarchy Process (AHP) is employed to establish a hierarchical human resource structure model to determine the relative weight of each HRM indicator. Subsequently, the FCE method is utilized to build an SMHR optimization model, which is then scrutinized and assessed by means of an example. The findings indicate that the consistency ratio (C.R.) values of the first and second-level evaluation factors of the constructed model are less than 0.1, thus passing the consistency test and demonstrating credibility. Ultimately, the research effectively grades SMHR in the enterprise through the analysis of HRM optimization. Accordingly, this research presents a set of optimization suggestions and measures, including the establishment of a professional HRM operation team, acceleration of the construction of a professional talent team, enhancement of the intelligent level of the HRM center, and transition towards digital sharing. These proposed measures can serve as valuable experimental references for the optimization and improvement of HRM structures in future enterprises.

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“…After decades of development and improvement, this theory has become an essential means to solve the problem of dynamic analyses of complex systems [32,33]. For example, Borutzky [34] et al used it for the modeling and analysis of the hydraulic system, Fu [35] et al used it for the modeling and simulation of the electric drive system, and Merahi [36,37] et al used the bond-graph theory for mathematical modeling in the field of chemical batteries and electric vehicles. Zhang [8,9] et al first used the bond-graph theory for the mathematical modeling of the ETD.…”

Section: Introductionmentioning

confidence: 99%

Energy Consumption Analysis of Helicopter Traction Device: A Modeling Method Considering Both Dynamic and Energy Consumption Characteristics of Mechanical Systems

et al. 2022

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Since modern times, the increase in shipborne equipment has brought tremendous pressure to the energy supply system. Establishing an accurate and reliable energy consumption model that reflects the dynamic characteristics of the system will provide an essential theoretical reference for energy efficiency optimization. This paper proposes a modeling method that considers both the dynamic characteristics and energy consumption characteristics of the system, based on the power bond-graph theory. Firstly, the transmission principle and energy transfer process of hydraulic and electric helicopter traction devices are analyzed. Then, the energy consumption is analyzed, and the state equation and energy equation of the system are established. Finally, the simulation tests are carried out. The results show that the proposed dynamic modeling method is reasonable and effective and can well reflect the dynamic characteristics and energy consumption characteristics of the system.

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Design and Validation of Energy Management Strategy for Extended-Range Fuel Cell Electric Vehicle Using Bond Graph Method

Cited by 11 publications

References 52 publications

Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming

Energy Management Optimization and Validation of a Hydrogen Fuel Cell-Powered Agricultural Tractor Based on Hierarchical Dynamic Programming

Fuzzy comprehensive evaluation and quantitative weight analysis in structure management of human resources

Energy Consumption Analysis of Helicopter Traction Device: A Modeling Method Considering Both Dynamic and Energy Consumption Characteristics of Mechanical Systems

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