低温区域燃料电池混合动力电动汽车的电热协同控制和多模式能量流分析

IF 15 1区 工程技术 Q1 ENERGY & FUELS Etransportation Pub Date : 2024-05-28 DOI:10.1016/j.etran.2024.100341
Xiao Yu , Cheng Lin , Peng Xie , Yu Tian , Haopeng Chen , Kai Liu , Huimin Liu
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引用次数: 0

摘要

电动汽车在各种推进模式和各种气候条件下运行时的能量流分布特征尚未得到深入探讨。要实现有效的电热协同能源管理,必须考虑各种气候条件,采用智能控制方法来缓解里程焦虑。在本研究中,我们基于改进的深度神经网络和能量量化模型,开发了一种新型电热协同能源管理策略,以提高全局能量转换效率。根据车辆控制单元收集的实验数据,总结了在-10°C-35°C温度范围内,各种策略和推进模式下的完整能耗分布特征,包括电池自加热、座舱加热、加速消耗和燃油消耗。我们的研究结果表明,对于燃料电池混合动力客车,在包括初始车厢加热过程的循环中,当环境温度为-2 ℃和-10 ℃时,纯电动模式下的加热消耗分别为 9.9 kWh/循环和 13 kWh/循环,分别占总消耗的 33% 和 42%。在使用燃料电池的余热后,相同条件下的电加热消耗仅为 3.7 千瓦时/周期。在高温情况下,车厢制冷消耗为 3.26 千瓦时/周期,仅占总能耗的 18%。最后,在低温情况下,电热协同战略在纯电动和混合动力模式下分别降低了 14.7% 和 9.2% 的成本。因此,我们的方法大大提高了能源利用率和转换效率,尤其是在低温条件下。
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Electric-thermal collaborative control and multimode energy flow analysis of fuel cell hybrid electric vehicles in low-temperature regions

The energy flow distribution characteristics of electric vehicles operating in various propulsion modes and all climatic scenarios have not been thoroughly explored. To achieve effective electric-thermal collaborative energy management, intelligent control methods must be applied considering various climatic conditions to alleviate mileage anxiety. In this study, we developed a novel electric–thermal collaborative energy management strategy based on an improved deep neural network and energy quantification model to increase the global energy conversion efficiency. The complete energy consumption distribution characteristics are summarized under various strategies and propulsion modes based on an experiment data collected by the vehicle control unit that involves battery self-heating, cabin heating, acceleration consumption, and fuel consumption in the temperature range of −10°C-35 °C. Our findings indicate that, for a fuel cell hybrid bus in the cycle including the initial cabin heating process, the heating consumption in the pure electric mode was 9.9 kWh/cycle and 13 kWh/cycle when the ambient temperature is −2 °C and −10 °C, respectively, accounting for 33 % and 42 % of the total consumption, respectively. After using the waste heat from the fuel cell, the consumption of electric heating under the same conditions is only 3.7 kWh/cycle. In the high-temperature scenario, the cabin cooling consumption is 3.26 kWh/cycle, accounting for only 18 % of the total energy consumption. Finally, in low-temperature scenarios, the electric–thermal collaborative strategy reduced the cost by 14.7 % and 9.2 % in the pure electric and hybrid modes, respectively. Thus, our approach significantly improves energy utilization and conversion efficiency, especially at low temperatures.

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来源期刊
Etransportation
Etransportation Engineering-Automotive Engineering
CiteScore
19.80
自引率
12.60%
发文量
57
审稿时长
39 days
期刊介绍: eTransportation is a scholarly journal that aims to advance knowledge in the field of electric transportation. It focuses on all modes of transportation that utilize electricity as their primary source of energy, including electric vehicles, trains, ships, and aircraft. The journal covers all stages of research, development, and testing of new technologies, systems, and devices related to electrical transportation. The journal welcomes the use of simulation and analysis tools at the system, transport, or device level. Its primary emphasis is on the study of the electrical and electronic aspects of transportation systems. However, it also considers research on mechanical parts or subsystems of vehicles if there is a clear interaction with electrical or electronic equipment. Please note that this journal excludes other aspects such as sociological, political, regulatory, or environmental factors from its scope.
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