一种充电主机柜防凝露的协同控制方法

By monitoring and predicting dew point temperature in real time, classifying condensation risk levels, and coordinating the control of internal circulation fans, heaters, and dehumidifiers, the problems of delayed condensation response and increased energy consumption in the charging main cabinet are solved, achieving intelligent coordinated control of anti-condensation and heat dissipation.

CN122143710BActive Publication Date: 2026-07-17HANGZHOU JIAWA NEW ENERGY TECH CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HANGZHOU JIAWA NEW ENERGY TECH CO LTD
Filing Date
2026-05-08
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Condensation is prone to occur in outdoor environments. Existing anti-condensation measures are slow to respond and cannot dynamically track dew point temperature. Local temperature differences and humidity gradients are not taken into account, resulting in condensation forming before control actions and increased energy consumption.

Method used

It uses temperature sensors and dew point meters for real-time monitoring, predicts future dew point temperatures based on historical dew point temperature data, classifies condensation risk levels, sets collaborative control cycles, and coordinates the working strategies of internal circulation fans, heaters, dehumidifiers, and ventilation regulating valves to achieve intelligent and automated temperature regulation.

Benefits of technology

Precisely control the temperature environment of the charging cabinet to prevent condensation from forming before control actions, reduce energy consumption, achieve a synergistic effect of condensation prevention and heat dissipation, and reduce manual intervention.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明公开了一种充电主机柜防凝露的协同控制方法,涉及充电桩技术领域,包括如下步骤:S1:在充电主机柜内部署温度传感器和露点仪,实时采集充电主机柜内的温度和露点温度,通过露点温度历史数据预测未来露点温度得到预测露点温度;通过将凝露风险划分为无风险等级、低级风险等级、中级风险等级和高级风险等级的四个凝露风险等级,从而便于后续根据凝露风险等级执行不同的协同控制策略,进而便于根据充电主机柜内的实时温度环境作出针对性的调整,进而便于监测数据、预测数据和加热器、除湿机、内循环风机以及通风调节阀机械设备相结合协调工作精准控制充电主机柜的温度环境,有益于避免数据孤岛化的同时便于实现智能自动化温度调节。
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