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main
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testing/la
@ -12,7 +12,7 @@
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#define RETURN_FLOW_TEMPERATURE_LOWER_LIMIT_DAY 30.0
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#define RETURN_FLOW_TEMPERATURE_LOWER_LIMIT_NIGHT 25.0
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#define CHAMPER_TEMPERATURE_TARGET 80.0
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#define CHAMPER_TEMPERATURE_TARGET 70.0
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#define BURNER_FAULT_DETECTION_THRESHOLD (60U * 3U) // Detect burner fault if after 3 minutes no burner start detected
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static const char *TAG = "smart-oil-heater-control-system-control";
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@ -98,7 +98,7 @@ void taskControl(void *pvParameters)
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if (bHeatingInAction == true)
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{
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if ((getChamberTemperature().fCurrentValue >= currentControlEntry.fChamberTemperature) || (getChamberTemperature().predict60s.fValue >= currentControlEntry.fChamberTemperature))
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if (getChamberTemperature().fCurrentValue >= currentControlEntry.fChamberTemperature)
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{
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ESP_LOGI(TAG, "Chamber Target Temperature reached: Disable burner");
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bHeatingInAction = false;
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@ -16,10 +16,10 @@ static const char *TAG = "smart-oil-heater-control-system-inputs";
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const uint8_t uBurnerFaultPin = 19U;
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const uint8_t uDS18B20Pin = 4U;
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const onewire_addr_t uChamperTempSensorAddr = 0xd00000108cd01d28;
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const onewire_addr_t uChamperTempSensorAddr = 0x78000000c6c2f728;
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const onewire_addr_t uOutdoorTempSensorAddr = 0x78000000c6c2f728;
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const onewire_addr_t uInletFlowTempSensorAddr = 0x410000108b8c0628;
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const onewire_addr_t uReturnFlowTempSensorAddr = 0x90000108cc77c28;
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const onewire_addr_t uInletFlowTempSensorAddr = 0x78000000c6c2f728;
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const onewire_addr_t uReturnFlowTempSensorAddr = 0x78000000c6c2f728;
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onewire_addr_t uOneWireAddresses[MAX_DN18B20_SENSORS];
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float fDS18B20Temps[MAX_DN18B20_SENSORS];
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@ -36,7 +36,7 @@ void taskInput(void *pvParameters);
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void initMeasurement(sMeasurement *pMeasurement);
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void updateAverage(sMeasurement *pMeasurement);
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void updatePrediction(sMeasurement *pMeasurement);
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float linearRegressionPredict(const float *samples, size_t count, size_t bufferIndex, float futureIndex);
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float linearRegressionPredict(const float *samples, size_t count, float futureIndex);
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void initInputs(void)
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{
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@ -162,7 +162,6 @@ void updatePrediction(sMeasurement *pMeasurement)
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predict60s->fValue = linearRegressionPredict(
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predict60s->samples,
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predict60s->bufferCount,
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predict60s->bufferIndex,
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predict60s->bufferCount + 60.0f);
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}
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@ -218,7 +217,7 @@ void taskInput(void *pvParameters)
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for (int j = 0; j < sSensorCount; j++)
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{
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float temp_c = fDS18B20Temps[j];
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// ESP_LOGI(TAG, "Sensor: %08" PRIx64 " reports %lf°C", (uint64_t)uOneWireAddresses[j], temp_c);
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ESP_LOGI(TAG, "Sensor: %08" PRIx64 " reports %lf°C", (uint64_t)uOneWireAddresses[j], temp_c);
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switch ((uint64_t)uOneWireAddresses[j])
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{
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@ -227,20 +226,17 @@ void taskInput(void *pvParameters)
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sChamperTemperature.state = MEASUREMENT_NO_ERROR;
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updateAverage(&sChamperTemperature);
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updatePrediction(&sChamperTemperature);
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break;
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case ((uint64_t)uOutdoorTempSensorAddr):
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sOutdoorTemperature.fCurrentValue = temp_c;
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sOutdoorTemperature.state = MEASUREMENT_NO_ERROR;
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updateAverage(&sOutdoorTemperature);
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updatePrediction(&sOutdoorTemperature);
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break;
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case ((uint64_t)uInletFlowTempSensorAddr):
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sInletFlowTemperature.fCurrentValue = temp_c;
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sInletFlowTemperature.state = MEASUREMENT_NO_ERROR;
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updateAverage(&sInletFlowTemperature);
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updatePrediction(&sInletFlowTemperature);
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break;
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case ((uint64_t)uReturnFlowTempSensorAddr):
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sReturnFlowTemperature.fCurrentValue = temp_c;
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sReturnFlowTemperature.state = MEASUREMENT_NO_ERROR;
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updateAverage(&sReturnFlowTemperature);
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@ -268,7 +264,7 @@ void taskInput(void *pvParameters)
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}
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}
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float linearRegressionPredict(const float *samples, size_t count, size_t bufferIndex, float futureIndex)
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float linearRegressionPredict(const float *samples, size_t count, float futureIndex)
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{
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if (count == 0)
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return 0.0f; // No prediction possible with no data
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@ -277,11 +273,8 @@ float linearRegressionPredict(const float *samples, size_t count, size_t bufferI
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for (size_t i = 0; i < count; i++)
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{
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// Calculate the circular buffer index for the current sample
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size_t circularIndex = (bufferIndex + i + 1) % count;
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float x = (float)i; // Time index
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float y = samples[circularIndex]; // Sample value
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float x = (float)i; // Time index
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float y = samples[i]; // Sample value
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sumX += x;
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sumY += y;
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@ -291,8 +284,8 @@ float linearRegressionPredict(const float *samples, size_t count, size_t bufferI
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// Calculate slope (m) and intercept (b) of the line: y = mx + b
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float denominator = (count * sumX2 - sumX * sumX);
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if (fabs(denominator) < 1e-6) // Avoid division by zero
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return samples[bufferIndex]; // Return the latest value as prediction
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if (fabs(denominator) < 1e-6) // Avoid division by zero
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return samples[count - 1]; // Return last value as prediction
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float m = (count * sumXY - sumX * sumY) / denominator;
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float b = (sumY - m * sumX) / count;
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