A method and system for diagnosing technical condition of charging pile based on deep neural network
A deep neural network and state-of-the-art technology, applied in electric vehicle charging technology, biological neural network models, charging stations, etc., can solve problems such as serious consequences and many failures, and achieve the effect of avoiding serious consequences
Active Publication Date: 2022-07-29
NARI NANJING CONTROL SYST +7
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Problems solved by technology
[0004] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a method and system for diagnosing the technical status of charging piles based on a deep neural network, so as to solve the problems of charging piles in the prior art caused by open circuit or short circuit of power devices. The technical problems with the most serious consequences and cannot be assessed and predicted in advance
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[0040] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solutions of the present invention more clearly, and cannot be used to limit the protection scope of the present invention.
[0041] The specific embodiment of the present invention provides a method for diagnosing the technical condition of a charging pile based on a deep neural network. value and ripple characteristics) to diagnose the operating status of the power devices in the charging pile.
[0042] The power module of the DC charging pile mainly includes three links: PWM rectification, filtering and high-frequency DC / DC power conversion, such as figure 1 shown is a schematic diagram of the topology principle of the three-phase PWM rectifier circuit in the embodiment of the present invention. In the figure, T 1 ~T 6 is the power device, U a , U b , U c is the three-phase input voltage, L a , L ...
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The invention discloses a method and system for diagnosing the technical condition of a charging pile based on a deep neural network in the technical field of fault detection, and aims to solve the problem that the charging pile in the prior art has the most faults and the most serious consequences due to the open circuit or short circuit of the power device. , and the predicted technical issues cannot be assessed in advance. The method includes the following steps: obtaining a voltage signal on the DC side of a target charging pile; inputting the voltage signal into a pre-trained deep neural network to obtain the probability of failure of a power device in the target charging pile.
Description
technical field [0001] The invention relates to a method and system for diagnosing the technical condition of a charging pile based on a deep neural network, and belongs to the technical field of fault detection. Background technique [0002] With the increasing maturity of power battery and fast charging technology, electric vehicles have become an important part of the automotive market. Electric vehicles convert electrical energy into mechanical energy to provide power, thereby replacing or partially replacing fossil energy, which is conducive to reducing dependence on petroleum resources, reducing exhaust pollution, improving atmospheric environment, and reducing carbon dioxide emissions. Because lithium-ion batteries have high power density and energy density, they are often used in power batteries for electric vehicles. Among them, lithium iron phosphate batteries have excellent cycle stability, and 72% of the power batteries on the market use lithium iron phosphate ba...
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IPC IPC(8): G06K9/00G06K9/62G06N3/04B60L53/62G01R31/379
CPCB60L53/62G01R31/379G06N3/045G06F2218/12G06F18/2415Y02T90/12
Inventor 陈良亮张浩张卫国杨凤坤郑红娟邵军军周静李化周材李明贞周承科
Owner NARI NANJING CONTROL SYST