Process for refrigerant charge level detection using a neural net

A process for determining the charge level of a vapor cycle environmental control system, having a condenser, evaporator, compressor, and an expansion valve comprising the steps of:

• providing a neural network having four input neurons, two hidden neurons and three output neurons;
• determining the number of degrees below the saturation temperature of the liquid refrigerant exiting the condenser and providing this measurement to the first input neuron;
• sensing the condenser sink temperature and providing the measurement to the second input neuron;
• sensing either the refrigerant outlet temperature from the condenser or the evaporator exhaust air temperature and providing the measurement to the third input neuron;
• sensing the evaporator air inlet temperature and providing the measurement to the fourth input neuron;
• training the neural network by providing under, over and normal refrigerant charge levels to the system and operating the system under varying operating conditions such that weighting factors for the neural network are determined;
• and
• using the trained neural network to monitor the charge level in the system.