电池管理系统算法基准 - 汽车应用的要求、方案和验证

IF 15 1区 工程技术 Q1 ENERGY & FUELS
Franziska Berger , Dominik Joest , Elias Barbers , Katharina Quade , Ziheng Wu , Dirk Uwe Sauer , Philipp Dechent
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引用次数: 0

摘要

状态估算器对于在实际应用中有效使用电池至关重要。算法不足会导致用户不满、安全风险和电池加速老化,给制造商带来巨大风险。为电池管理系统(BMS)开发算法包括定义需求、实施算法和验证算法,这是一个复杂的过程。BMS 算法的性能受到硬件、数据存储、开发和使用过程中的校准过程以及成本等方面制约因素的影响。此外,状态估计方法千差万别,需要特定的数据来影响算法性能。本研究调查了状态估计器开发过程中的这些复杂性,并强调了其性能的重要性。我们在专家访谈的基础上建立了一种选择测试场景的方法,该方法考虑了计算能力和具体应用场景。我们引入了基于模型的模拟环境,以处理复杂的验证工作。该环境可在实际应用条件、不同测试场景和参数变化下对算法进行全面验证。我们在不同条件和电池变化下对三种充电状态(SoC)估计器进行了示范性验证。结果表明,性能取决于温度、电池化学性质、初始 SoC 和测量误差。此外,电池与电池之间的变化凸显了算法验证的复杂性和工作量。引入额外的场景参数扩大了测试场景的范围,强调了选择能准确反映现场条件和最坏情况的场景的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Benchmarking battery management system algorithms - Requirements, scenarios and validation for automotive applications

State estimators are crucial for the effective use of batteries in real-world applications. Insufficient algorithms can lead to user dissatisfaction, safety risks, and accelerated battery degradation, posing significant risks to manufacturers. Developing algorithms for battery management systems (BMS) involves defining requirements, implementing algorithms, and validating them, which is a complex process. The performance of BMS algorithms is influenced by constraints related to hardware, data storage, calibration processes during development and use, and costs. Additionally, state estimation methods vary widely, requiring specific data that impact algorithm performance.

This study investigates these complexities in the development of state estimators and underscores the importance of their performance. We established an approach for selecting test scenarios, based on expert interviews, which considers computational capabilities and specific application scenarios. A model-based simulation environment is introduced to handle the complexities of validation. This environment enables thorough validation of the algorithms under real-application conditions, different test scenarios, and parameter variations.

We exemplarily perform a validation for three State of Charge (SoC) estimators under diverse conditions and cell variations. The results show the performance dependencies on temperatures, cell chemistries, initial SoCs and measurement inaccuracies. Additionally, the cell-to-cell variations highlight the complexity and effort of algorithm validation. Introducing an additional scenario parameter expands the range of test scenarios, emphasizing the necessity to select scenarios that accurately reflect field conditions and worst-case situations.

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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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