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我们如何基于控制器局域网总线数据校准电池电动汽车模型?

How Do We Calibrate a Battery Electric Vehicle Model Based on Controller Area Network Bus Data?

作者信息

Tollner Dávid, Nyerges Ádám, Jneid Mahmoud Said, Geleta Attila, Zöldy Máté

机构信息

Department of Automotive Technologies, Budapest University of Technology and Economics, 1111 Budapest, Hungary.

Robert Bosch Kft., 1103 Budapest, Hungary.

出版信息

Sensors (Basel). 2024 Jul 17;24(14):4637. doi: 10.3390/s24144637.

DOI:10.3390/s24144637
PMID:39066035
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11280882/
Abstract

Transforming an up-to-date vehicle into a measurement system is a rewarding task due to the large number of different sensors in the onboard control and diagnostic systems. These procedures are not performed by a single control unit; it is necessary to share the signal values over a communication network, to which an external device can be connected to record the real traffic. The paper aims to use these recorded data for 1 DOF longitudinal vehicle and powertrain model validation. For repeatability, three city routes are selected: plain road, smaller road grade, and higher road grade in both directions. Therefore, the drivetrain system is tested in a high load range, even with long-term recuperation. The altitude changes are recorded with a DGPS system. By the recorded measurements, the vehicle and the drivetrain model can be calibrated, such as the air drag parameters, the rolling resistances, and the efficiencies of the drivetrain. The validation criteria are defined for speed tracking, and the relative tolerance of the cumulated energy should be below 10%. At the end of the day, a developed model is ready for energetic analysis or control strategy design. The energy balance of the applied cycles is also presented to prove that.

摘要

由于车载控制和诊断系统中有大量不同的传感器,将一辆最新的车辆转变为一个测量系统是一项很有意义的任务。这些程序并非由单个控制单元执行;有必要通过通信网络共享信号值,外部设备可以连接到该网络以记录实际交通情况。本文旨在将这些记录的数据用于单自由度车辆纵向和动力总成模型的验证。为了实现可重复性,选择了三条城市路线:平坦道路、较小坡度道路和双向的较大坡度道路。因此,即使在长期能量回收的情况下,传动系统也能在高负载范围内进行测试。海拔变化通过差分全球定位系统(DGPS)进行记录。通过记录的测量数据,可以对车辆和传动系统模型进行校准,如空气阻力参数、滚动阻力以及传动系统的效率。为速度跟踪定义了验证标准,累积能量的相对公差应低于10%。在一天结束时,一个开发好的模型可用于能量分析或控制策略设计。还展示了所应用循环的能量平衡以证明这一点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/ca79b76c1e20/sensors-24-04637-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/1d1e6b8762e4/sensors-24-04637-g006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/ca79b76c1e20/sensors-24-04637-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/aad89b815b0f/sensors-24-04637-g0A1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/3e93d8776d3e/sensors-24-04637-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/9e6d9ce6acfb/sensors-24-04637-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/1d1e6b8762e4/sensors-24-04637-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/55582787c0ff/sensors-24-04637-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/784e3beb5130/sensors-24-04637-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/7972495010df/sensors-24-04637-g009.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/695b/11280882/ca79b76c1e20/sensors-24-04637-g012.jpg

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Health State Estimation of On-Board Lithium-Ion Batteries Based on GMM-BID Model.基于 GMM-BID 模型的车载锂离子电池健康状态估计。
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