Component-level analysis for developing an energy consumption model for battery electric vehicles (BEVs) in operation

IF 17 1区 工程技术 Q1 ENERGY & FUELS
Dongmin Kim, Kitae Jang
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引用次数: 0

Abstract

In battery electric vehicles (BEV), energy originates in the battery and is transmitted to the wheels through a series of energy conversion processes involving the inverter and motor. Therefore, understanding the energy conversion mechanisms in both the inverter and motor is essential for accurately modeling energy consumption. However, in previous studies, real-world driving data are often limited, making it challenging to fully analyze the complex and nonlinear relationships within each conversion component. In this study, we collected input–output data from the inverters and motors of fifty-four BEVs, measured repeatedly over time. The data revealed a piecewise nonlinear relationship between input and output, prompting us to partition the models by different phases: propulsion, regeneration, and battery status. For each phase, we applied linear mixed-effects models to account for the hierarchical structure of the data, estimating coefficients separately for the inverter and motor using a randomly selected 75% of the dataset. Through this component-level modeling approach, the models not only capture component-level random-effect parameters but also effectively model the nonlinear energy conversion characteristics at the component level. The two models were then integrated to estimate the total driving energy consumption of the BEVs, and the results were validated against actual observations using the total driving energy from the remaining 25% of the dataset. Model performance was evaluated using the Total Consumption Estimation Rate (TCER) and Mean Absolute Percentage Error (MAPE). The proposed model achieved at least 95.27% in TCER and 86.34% in MAPE, outperforming existing approaches with a 20% higher TCER and an MAPE approximately ten times lower on average. The comparison demonstrated that our model accurately estimates driving energy consumption, as it effectively captured the heterogeneous and nonlinear relationships between input and output energy for each component.
基于组件级分析的纯电动汽车运行能耗模型开发
在纯电动汽车(BEV)中,能量来源于电池,并通过一系列涉及逆变器和电机的能量转换过程传递给车轮。因此,了解逆变器和电机的能量转换机制对于准确建模能量消耗至关重要。然而,在以往的研究中,真实驾驶数据往往是有限的,因此很难充分分析每个转换组件之间复杂的非线性关系。在这项研究中,我们收集了54辆纯电动汽车的逆变器和电机的输入输出数据,并在一段时间内反复测量。数据揭示了输入和输出之间的分段非线性关系,促使我们根据不同的阶段划分模型:推进,再生和电池状态。对于每个阶段,我们应用线性混合效应模型来解释数据的层次结构,使用随机选择的75%的数据集分别估计逆变器和电机的系数。通过构件级建模方法,模型不仅可以捕获构件级的随机效应参数,而且可以有效地模拟构件级的非线性能量转换特性。然后将这两个模型整合起来估算纯电动汽车的总驾驶能耗,并使用剩余25%的数据集中的总驾驶能耗对实际观测结果进行验证。使用总消耗估计率(TCER)和平均绝对百分比误差(MAPE)评估模型性能。该模型的TCER和MAPE分别达到95.27%和86.34%,优于现有的TCER高20%、MAPE平均低约10倍的方法。比较表明,我们的模型准确地估计了驱动能量消耗,因为它有效地捕获了每个组件的输入和输出能量之间的异质性和非线性关系。
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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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