The core of the intelligent adaptation strategy of solar inverter temperature control is to make the temperature control system automatically adjust according to the changes of load, environment and device state through sensor data acquisition and algorithm dynamic decision, so as to realize "heat dissipation on demand and optimal efficiency". The following are the specific classification and implementation details:
First, the load-temperature linkage adaptation strategy
The core of this strategy is to predict the heating trend according to the real-time load rate of the inverter and adjust the heat dissipation scheme in advance to avoid the inefficient problem of "passive heat dissipation after sudden temperature rise".
Load rate grading heat dissipation rule
The heating power of the inverter is positively related to the load rate (the higher the load rate, the greater the switching loss and conduction loss of IGBT), and the adaptation is realized by preset load-heat dissipation linkage threshold:
Load rate < 30% (light load): the core device generates low heat, and the fan runs or stops at a low speed, only relying on passive heat dissipation;
30%≤ Load rate < 70% (medium load): The fan runs at a medium speed, and the temperature of core components is maintained at 30-35℃;
Load rate ≥70% (heavy load): increase the fan speed/liquid cooling flow rate in advance (without waiting for the temperature to rise), and predict the cooling to prevent the temperature from exceeding the threshold quickly;
Response to sudden load change: When the load rate increases by more than 40% within 10 seconds, the fan is directly triggered to run at full speed to avoid device damage caused by transient heating.
Dynamic start-stop adaptation of multi-module inverter
Aiming at the high-power parallel inverter, the power module is intelligently started and stopped according to the load;
Turn off redundant modules under light load to reduce standby heating and reduce overall heat dissipation pressure;
When overloaded, start all modules step by step to balance the temperature of each module and avoid overloading and overheating of a single module.
Second, the adaptive adaptation strategy of environmental parameters
According to the variables of outdoor installation environment, such as temperature, wind speed and sunshine, the temperature control strategy is dynamically adjusted to maximize the use of natural environment to assist heat dissipation and reduce the power consumption of active heat dissipation.
Environmental temperature compensation adaptation
The ambient temperature varies greatly in different seasons/regions, so the heat dissipation threshold is corrected by the data of the ambient temperature sensor:
Low temperature environment (< 10℃): raise the threshold of fan starting temperature (for example, from 35℃ to 40℃), give priority to natural low temperature heat dissipation, and reduce the running time of fans;
High temperature environment (> 35℃): lower the starting threshold of the fan (for example, from 35℃ to 30℃), and start the cooling system in advance to prevent overheating and load reduction caused by the heating of the superimposed devices in high temperature environment;
Temperature difference adaptation between day and night: the ambient temperature is low at night, which automatically reduces the liquid cooling flow/fan speed; During the high temperature period during the day, strengthen the heat dissipation power.
Linkage adaptation of wind speed and sunshine
Wind speed assisted cooling: when the outdoor wind speed is ≥3m/s, reducing the fan speed and using natural wind to strengthen convection cooling in the air duct can reduce the active cooling power consumption by 10%–15%;
Sunlight avoidance adaptation: the direct intensity is monitored by the sunlight sensor, and when the temperature of the enclosure rises due to the strong sunlight, the cooling power is automatically increased, and at the same time, the inverter power output limit (short-term small load shedding) is linked to avoid the double pressure of "high ambient temperature+device heating".
Third, the device state self-sensing adaptation strategy
Based on the real-time temperature and aging data of core components, the temperature control strategy is dynamically adjusted, taking into account efficiency and device life.
Accurate adaptation of multipoint temperature measurement
Abandoning the limitation of traditional "single-point temperature measurement", sensors are deployed in key parts such as IGBT junction temperature, transformer winding and capacitor shell to realize differential temperature control;
When the IGBT junction temperature is close to the threshold (such as 100℃), the heat dissipation power in this area (such as the flow rate of liquid cooling plate) should be given priority, rather than the heat dissipation of the whole machine;
When the capacitor temperature is high (affecting the life), appropriately reduce the inverter high-frequency switching frequency, reduce the capacitor loss, and strengthen local heat dissipation.
Adaptive adjustment of device aging
Combined with the long-term operation data, identify the aging trend of devices (such as the attenuation of capacitance and the increase of IGBT internal resistance, which will lead to the increase of heating):
For the area where the aging device is located, the heat dissipation priority is automatically increased to extend the remaining service life of the device;
The temperature control threshold is corrected by algorithm to avoid temperature misjudgment caused by device aging.
