本文致力于电池管理系统设计及电池荷电状态(SOC)估算的研究。
This article dedicated to the research on the design of battery management system and battery state of charge (SOC) estimation.
为了准确预测使用过程中的电池荷电状态，提出了电化学阻抗谱预测法。
For predicting the state of charge (SOC) of lithium-ion rechargeable battery accurately, a method based on electrochemical impedance spectroscopy was presented.
电动车电池管理系统的核心任务是对电池荷电状态（SOC）进行预测。
The state-of-charge(SOC) is an important parameter for the electrical vehicle.
在蓄电池的使用和研究过程中，其荷电状态的准确判断已经变得越来越重要。
During the process of the battery's utilization and research, the accurate judgement of its charged state becomes more and more important.
然而，荷电状态为不可直接测量的参数，只能通过其它可获取信息对其进行估计。
However, SOC can not be measured directly but estimated from other acquirable information.
本文介绍了估算电池荷电状态(SOC)的常用方法，分析了这些方法的优缺点。
Firstly, this thesis introduces several kinds of SOC measuring methods and analyzes their advantages and disadvantages.
铅酸电池的荷电状态(SOC)的测量和估计，对电动汽车的电池管理系统极为重要。
It was very importance for the battery management system in electric vehicles to measure and estimate the state of charge (SOC) of lead-acid batteries.
根据所选用的单体镍氢电池的特点，以及荷电状态SOC均衡方法来确定电池包参数测量点的数量。
According to feature of individual battery and equalization method for state of charge (SOC), the number of measuring points is determined.
现有电池荷电状态(SOC)估计方法所需训练和学习时间较长，很难满足动力电池的实时性要求。
Existing battery State of Charge (SOC) estimation methods are time consuming for the training and learning process, and it restricts the application in electrical vehicles.
提出了一种星上电池均衡控制的方法，此方法可在充电与放电状态下，根据每节电池各自的荷电状态对整组串联电池组进行有效均衡。
Based on the model, a new method to control battery equalization was present to counterpoise the energy of in the same battery team in series both for charging state and discharging state.
在部分荷电状态（PSOC）下采用不同的充电模式，进行了100%放电深度的对比试验，同时对失效单体电池进行了容量恢复实验。
Under the partial state of charge (PSOC) condition, the experiments for 100% depth of discharge were carried out by using different charging algorithms.
因而不能用铅蓄电池的电导值去推断在线使用的铅电池的荷电态或健康状态。
For this reason the state-of-charge or state-of-health for on-line batteries could not be predicted from it's values of conductance.
因而不能用铅蓄电池的电导值去推断在线使用的铅电池的荷电态或健康状态。
For this reason the state-of-charge or state-of-health for on-line batteries could not be predicted from it's values of conductance.
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