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基于预充电模型与RSNA的直流支撑电容器电容量辨识方法 被引量:2
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作者 伍珣 于天剑 +1 位作者 李凯迪 田睿 《铁道科学与工程学报》 EI CAS CSCD 北大核心 2023年第7期2664-2675,共12页
直流支撑电容器是牵引变流系统的关键器件,也是极易出现故障的电气部件。由于电压、充放电频率、温度等因素的影响,电容器的老化速度加快,其实际寿命与制造商手册中的数据相差很大。因此,有必要对直流支撑电容器状态进行辨识,从而保障... 直流支撑电容器是牵引变流系统的关键器件,也是极易出现故障的电气部件。由于电压、充放电频率、温度等因素的影响,电容器的老化速度加快,其实际寿命与制造商手册中的数据相差很大。因此,有必要对直流支撑电容器状态进行辨识,从而保障列车牵引变流系统安全运行。目前,已有较多学者对电容器状态辨识开展研究。但是,铁路应用中的直流支撑电容器状态辨识噪声问题尚未得到很好的解决。在某些情况下,电压传感器测量噪声与电压纹波分量相近会导致直流支撑电容器状态辨识结果出现较大偏差。针对上述问题,提出一种基于预充电模型与递推随机牛顿法(RSNA)的直流支撑电容器电容量辨识方法。在利用现有电压传感器信号以及不对原有系统进行改动的前提下建立电容器预充电模型,采用RSNA算法对电容量进行参数辨识,可以有效抵御噪声干扰并实现电容量的准确估计。该方法原理简单、计算量小,不需要加装额外传感器,以较低的采样频率即可达到较高的计算精度。同时,该方法不易受信噪比(SNR)与信号偏移等的影响,具有较好的鲁棒性。验证结果表明,该方法在正常情况下的辨识误差可以控制在3%以内,在信噪比为35 dB时仍然可以保持在5%左右,当信号偏移达到±10 V时可以保持在3%左右。 展开更多
关键词 电容器 状态辨识 预充电模型 RSNA
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Impact of Electric Vehicles on Travel and Electricity Demand in Metropolitan Area: A Case Study in Nagoya
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作者 Ryo Kanamori Takayuki Morikawa +2 位作者 Masaya Okumiya Toshiyuki Yamamoto Takayuki Ito 《Journal of Civil Engineering and Architecture》 2015年第3期341-349,共9页
In this study, we examine the impacts that EVs (electric vehicles) have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individua... In this study, we examine the impacts that EVs (electric vehicles) have on vehicle usage patterns and environmental improvements, using our integrated travel demand forecasting model, which can simulate an individual activity-travel behavior in each time period, as well as consider an induced demand by decreasing travel cost. In order to examine the effects that charging/discharging have on the demand in electricity, we analyze scenarios based on the simulation results of the EVs' parking location, parking duration and the battery state of charge. From the simulation, result under the ownership rate of EVs in the Nagoya metropolitan area in 2020 is about 6%, which turns out that the total CO2 emissions have decreased by 4% although the situation of urban transport is not changed. After calculating the electricity demand in each zone using architectural area and basic units of hourly power consumption, we evaluate the effect to decrease the peak load by V2G (vehicle-to-grid). According to the results, if EV drivers charge at home during the night and discharge at work during the day, the electricity demand in Nagoya city increases by approximately 1%, although changes in each individual zone range from -7% to +8%, depending on its characteristics. 展开更多
关键词 Electric vehicle integrated travel demand forecasting model electricity demand V2G.
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