Optimization of Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Based on Dynamic Programming

Du, Changqing; Huang, Shiyang; Jiang, Yuyao; Wu, Dongmei; Li, Yang

doi:10.3390/en15124325

Cited by 47 publications

(16 citation statements)

References 46 publications

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“…DC/DC converter has the function of regulating voltage and improving power supply quality. Therefore, the power system of this structure can provide stable current, reduce the voltage level of energy source and other performance requirements accordingly, and it is easy to realize the control of power size and direction between energy sources [17][18]. However, because the DC/DC converter will lose some power, the net output efficiency of this structure is slightly lower than that of the above two…”

Section: Figure 1 Fc Direct Connection Topologymentioning

confidence: 99%

Fuel Cell in Hybrid Electric Vehicle with Artificial Fish Swarm Algorithm

2020

KME

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Because of the slow dynamic response and poor stability of fuel cell(FC), composite power system is considered as a good solution. However, the complex energy storage makes the power and energy flow of the power system more complex, and new technologies are urgently needed to solve the problem of multi-mode energy distribution. Only by formulating efficient and reasonable energy management and optimization strategies can the performance and advantages of the complex power system be fully exploited. In this paper, the hybrid power system of FC vehicle is analyzed firstly, and the dual DC/DC converter structure is used as the research model. In order to reduce the operating cost of the system, the artificial fish swarm algorithm was introduced into the application scenario of FC tram, and the global optimal energy management strategy was proposed. The experimental results show that the ability management strategy based on artificial fish swarm algorithm is more effective in improving fuel economy.

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Section: Figure 1 Fc Direct Connection Topologymentioning

confidence: 99%

Fuel Cell in Hybrid Electric Vehicle with Artificial Fish Swarm Algorithm

2020

KME

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“…Another application could be the offline tuning of heuristic, and rule-based strategies, which are then implemented to online powertrain control [260]. For higher fuel economy and powertrain durability, Du et al have used DP to optimise a rule-based energy management strategy applied to an FCEV and have shown up to 6.46% improvement over fixed RBS while running Worldwide Harmonized Light-duty Test Cycle cycle [261]. When applying DP to actual powertrain management problems, drive cycle or route prediction uncertainty can be covered by introducing probability-based stochastic variables, making it Stochastic DP [231].…”

Section: Dynamic Programming (Dp)mentioning

confidence: 99%

A Review of Fuel Cell Powertrains for Long-Haul Heavy-Duty Vehicles: Technology, Hydrogen, Energy and Thermal Management Solutions

et al. 2022

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Long-haul heavy-duty vehicles, including trucks and coaches, contribute to a substantial portion of the modern-day European carbon footprint and pose a major challenge in emissions reduction due to their energy-intensive usage. Depending on the hydrogen fuel source, the use of fuel cell electric vehicles (FCEV) for long-haul applications has shown significant potential in reducing road freight CO2 emissions until the possible maturity of future long-distance battery-electric mobility. Fuel cell heavy-duty (HD) propulsion presents some specific characteristics, advantages and operating constraints, along with the notable possibility of gains in powertrain efficiency and usability through improved system design and intelligent onboard energy and thermal management. This paper provides an overview of the FCEV powertrain topology suited for long-haul HD applications, their operating limitations, cooling requirements, waste heat recovery techniques, state-of-the-art in powertrain control, energy and thermal management strategies and over-the-air route data based predictive powertrain management including V2X connectivity. A case study simulation analysis of an HD 40-tonne FCEV truck is also presented, focusing on the comparison of powertrain losses and energy expenditures in different subsystems while running on VECTO Regional delivery and Longhaul cycles. The importance of hydrogen fuel production pathways, onboard storage approaches, refuelling and safety standards, and fleet management is also discussed. Through a comprehensive review of the H2 fuel cell powertrain technology, intelligent energy management, thermal management requirements and strategies, and challenges in hydrogen production, storage and refuelling, this article aims at helping stakeholders in the promotion and integration of H2 FCEV technology towards road freight decarbonisation.

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“…The instantaneous hydrogen consumption rate fc m and the efficiency fcs η of the fuel cell system can be defined in Formula (24) [42,43], as shown in Figure 10b.…”

Section: Motor Modelmentioning

confidence: 99%

Research on Energy Consumption Generation Method of Fuel Cell Vehicles: Based on Naturalistic Driving Data Mining

Wang

et al. 2022

Machines

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In this paper, an energy consumption generation method is proposed to accurately calculate the energy consumption of fuel cell vehicles (FCVs). A specific driver drives on a route (from Jilin University to FAW Volkswagen) for 331 working days (1 April 2020 to 28 July 2021) and collects more than 40,000 s of naturalistic driving data by means of a GPS receiver (FRII-D). To accurately calculate the energy consumption data of FCVs under actual driving cycles, naturalistic driving data mining is first studied. The principal component analysis (PCA) algorithm is used to reduce the dimension of the extracted driving cycle characteristic parameters, the K-means algorithm is used for driving cycle clustering, and the LVQ is used for driving cycle identification. Then, the characteristic parameters correlated to energy consumption are obtained based on the FCV model and regression analysis method. In addition, an energy consumption generation method is designed and proposed based on the characteristic parameters and identification results. Furthermore, the proposed energy consumption generation method can accurately calculate the energy consumption of FCVs, which also provides a reference for further research on the efficient energy management of FCVs.

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Optimization of Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Based on Dynamic Programming

Cited by 47 publications

References 46 publications

Fuel Cell in Hybrid Electric Vehicle with Artificial Fish Swarm Algorithm

Fuel Cell in Hybrid Electric Vehicle with Artificial Fish Swarm Algorithm

A Review of Fuel Cell Powertrains for Long-Haul Heavy-Duty Vehicles: Technology, Hydrogen, Energy and Thermal Management Solutions

Research on Energy Consumption Generation Method of Fuel Cell Vehicles: Based on Naturalistic Driving Data Mining

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