| ID | 原文 | 译文 |
| 493 | 锂离子电池具有循环寿命长、能量密度高、自放电率低、环境污染小等优点，在电动汽车产业中得到广泛应用。 | Lithium-ion battery has been widely used in electric vehicle industry because of its long cycle life,high energy density, low self-discharge rate and low environmental pollution. |
| 494 | 电动汽车中的电池管理系统(BMS)可以维护和监测电池状态，确保电池的安全性和可靠性。 | The Battery Management System(BMS) in electric vehicles can maintain and monitor the battery status to ensure the security and reliability ofthe battery. |
| 495 | 电池荷电状态(SoC)表示电池中剩余的电量，是BMS的重要参数之一，实时精确的SoC估算可以延长电池寿命，保障行驶安全。 | The battery’s State of Charge (SoC) represents the remaining power in the battery and is one ofthe important parameters of the BMS. Real-time and accurate SoC estimation can extend battery life andensure driving safety. |
| 496 | 然而锂离子电池是一个高度复杂的非线性时变系统，电池寿命、环境温度、电池自放电等许多未知因素均会对估算精度造成影响，使估算难度大大增加。 | However, Lithium-ion battery is indeed a highly complex nonlinear time-varying system,many unknown factors, such as battery life, ambient temperature, battery self-discharge and so on, will affectthe estimation accuracy, which greatly increases the difficulty of estimation. |
| 497 | 为了满足不同条件下对锂离子电池SoC精确、快速、实时估算的要求，需要对SoC估计算法进行进一步研究与改进。 | To meet the requirements ofaccurate, rapid and real-time SoC estimation for Lithium-ion batteries under different conditions, furtherresearch and improvement of SoC estimation algorithm are needed. |
| 498 | 近年来已有相关文献对锂离子电池SoC的估算方法进行了综述，然而已有相关综述对估算方法的总结不够全面且缺少流程表达。 | In recent years, some review literature onthe Lithium-ion battery SoC estimation has been published. However, the existing literature has not summarized the estimation methods comprehensively and lack of process description. |
| 499 | 该文首先介绍了锂离子电池的工作原理，阐述了影响电池SoC估算的因素；其次，通过总结最新的研究成果对电池SoC估算方法进行了归纳分析，根据各类算法的不同特性将其分为查表法、安时积分法、基于模型的方法、数据驱动的方法以及混合方法五大类，说明了各类估算方法的主要特征并对模型或算法的优缺点进行综合的比较和讨论；最后，对电动汽车中锂离子电池SoC估算方法的未来发展方向做出展望。 | In this paper, the working principle ofLithium-ion battery is firstly introduced, as well as the factors affecting the SoC estimation of battery.Secondly, summary and analysis of the battery SoC estimation methods are conducted by the latest researchachievement. According to the different characteristics of various algorithms, the battery SoC estimation can bedivided into five categories: look-up table method, ampere hour integration method, model-based method, data-driven method and hybrid method. The main characteristics of various estimation methods are explained andthe advantages and disadvantages of models or algorithms are comprehensively compared and discussed.Finally, the future development direction of SoC estimation methods for Lithium-ion batteries in electricvehicles is prospected. |
| 500 | 针对激光测振系统中散斑效应导致的语音脉冲噪声，该文研究了一种基于4阶累积量的峰度检测算法，推导了峰度系数和归一化峰度系数的数学迭代公式，并在FPGA的实现中提出了一种峰度系数的动态阈值的判决方法。 | For the speech impulse noise caused by the speckle effect in the laser vibration measurement system,a kurtosis detection algorithm based on the fourth-order cumulant is studied, and the mathematical iterativeformulas for the kurtosis coefficient and the normalized kurtosis coefficient are deduced, and a method fordetermining the dynamic threshold of kurtosis coefficient is proposed in FPGA. |
| 501 | 基于实验数据的仿真结果表明，该算法较理论公式减少了约25%的计算量，节省了硬件资源，对较小幅度的脉冲噪声具有更敏感的检测性能。 | The simulation results based onexperimental data show that the algorithm reduces the calculation by about 25% compared with the theoreticalformula and saves hardware resources, and has a more sensitive detection performance for lower amplitudeimpulse noise. |
| 502 | 针对签名验签速度难以满足特定应用领域需求的问题，该文设计了一种高性能Ed25519算法的硬件实现架构。 | The speed of existing signature and verification architecture is difficult to meet the requirement of thespecific applications domain, to solve this problem a high-performance hardware architecture of Ed25519 algorithmis developed. |