fototeddyandClaude Sonnet 5
6d7b32d622
App: - New DeviceRole.solar with its own BLE session/protocol/state (SolarSession, VanAlignSolarProtocol, SolarState), mirroring the leveling sensor but deliberately not wired into the Live Activity. - BluetoothManager now keeps an in-memory history per metric (voltage, current, power) instead of a single primary-metric series; cleared on app restart by design, not persisted to disk. - DeviceDetailView shows a channel picker above the history chart when a device has more than one chartable metric. - AddDeviceView recognizes the solar service UUID during setup. - DemoData gets a simulated solar device so the integration can be checked in the simulator without hardware. Firmware: - Add esp32_ble_solar.yaml (Votronic solar charge controller over BLE) and simulated variants (esp32_ble_sim.yaml, esp32_ble_solar_sim.yaml) for testing without a vehicle. - esp32_ble.yaml: set flash_size/psram for the ESP32-S3 N16R8 module. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
333 lines
11 KiB
YAML
333 lines
11 KiB
YAML
# VanAlign Pro - Neigungsmessung über BLE (SIMULATION)
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#
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# Kopie von esp32_ble.yaml für den Fall, dass gerade kein MPU6050 zum
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# Anschliessen vorhanden ist. Der `platform: mpu6050`-Sensor sowie der
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# i2c-Bus wurden entfernt und durch Template-Sensoren ersetzt, die
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# plausible, sich langsam ändernde Beschleunigungswerte erzeugen (ein
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# gedachter Sensor, der gemütlich hin- und herschaukelt). Pitch/Roll,
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# Kalibrierung und die BLE-Charakteristiken funktionieren dadurch exakt wie
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# im Original - nur eben ohne angeschlossene Hardware.
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#
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# Name und Friendly Name sind bewusst auf "-sim" abgeändert, damit dieses
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# Gerät im Netzwerk/BLE nicht mit einem echten VanAlign-Gerät kollidiert.
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#
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# Sobald wieder ein echter MPU6050 verfügbar ist, einfach esp32_ble.yaml
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# weiterverwenden - diese Datei ist nur zum Testen der App/BLE-Anbindung.
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esphome:
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name: vanalign-sim
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friendly_name: "VanAlign Pro (Sim)"
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esp32:
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board: esp32-s3-devkitc-1
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flash_size: 16MB
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framework:
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type: esp-idf
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# N16R8: 16 MB Flash + 8 MB PSRAM, beim S3 als Octal-PSRAM angebunden.
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psram:
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mode: octal
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speed: 80MHz
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logger:
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level: WARN
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espnow:
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channel: 1
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sensor:
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# Simulierte Rohwerte anstelle des physischen MPU6050. Die Sensor-Lage
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# (Pitch/Roll) wandert langsam und stetig, wie es ein tatsächlich leicht
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# schaukelndes Fahrzeug/Werkstück tun würde (Perioden ~75s/~113s).
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- platform: template
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name: "MPU6050 Accel X (Sim)"
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id: accel_x
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internal: true
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update_interval: 0.1s
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lambda: |-
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float t = millis() / 1000.0f;
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float pitch_rad = (15.0f * sin(t / 12.0f)) * 3.14159265f / 180.0f;
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float roll_rad = (10.0f * sin(t / 18.0f + 1.0f)) * 3.14159265f / 180.0f;
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return -9.80665f * sin(roll_rad) * cos(pitch_rad);
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- platform: template
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name: "MPU6050 Accel Y (Sim)"
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id: accel_y
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internal: true
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update_interval: 0.1s
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lambda: |-
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float t = millis() / 1000.0f;
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float pitch_rad = (15.0f * sin(t / 12.0f)) * 3.14159265f / 180.0f;
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return 9.80665f * sin(pitch_rad);
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- platform: template
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name: "MPU6050 Accel Z (Sim)"
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id: accel_z
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internal: true
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update_interval: 0.1s
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lambda: |-
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float t = millis() / 1000.0f;
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float pitch_rad = (15.0f * sin(t / 12.0f)) * 3.14159265f / 180.0f;
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float roll_rad = (10.0f * sin(t / 18.0f + 1.0f)) * 3.14159265f / 180.0f;
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return 9.80665f * cos(roll_rad) * cos(pitch_rad);
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# Gyro-Werte werden nur zur Anzeige simuliert (kleine Winkelgeschwindigkeit
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# passend zur Schaukelbewegung oben, kein realer Bezug nötig).
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- platform: template
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name: "MPU6050 Gyro X-Achse"
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id: mpu_gyro_x
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update_interval: 0.1s
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lambda: |-
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float t = millis() / 1000.0f;
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return (10.0f / 18.0f) * cos(t / 18.0f + 1.0f) * 3.14159265f / 180.0f;
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- platform: template
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name: "MPU6050 Gyro Y-Achse"
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id: mpu_gyro_y
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update_interval: 0.1s
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lambda: |-
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float t = millis() / 1000.0f;
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return (15.0f / 12.0f) * cos(t / 12.0f) * 3.14159265f / 180.0f;
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- platform: template
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name: "MPU6050 Gyro Z-Achse"
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id: mpu_gyro_z
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update_interval: 0.1s
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lambda: |-
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return 0.0f;
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- platform: template
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name: "Neigung Pitch"
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id: pitch
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icon: mdi:caravan
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unit_of_measurement: "°"
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accuracy_decimals: 1
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update_interval: 0.1s
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lambda: |-
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if (isnan(id(accel_x).state) || isnan(id(accel_y).state) || isnan(id(accel_z).state)) {
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return NAN;
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}
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float raw = atan2(id(accel_y).state, sqrt(pow(id(accel_x).state, 2) + pow(id(accel_z).state, 2))) * (180.0 / 3.14159265);
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return raw - id(pitch_offset); // Offset wird hier subtrahiert
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filters:
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- sliding_window_moving_average:
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window_size: 8
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send_every: 1
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- exponential_moving_average:
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alpha: 0.2
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- platform: template
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name: "Neigung Roll"
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id: roll
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icon: mdi:axis-x-rotate-clockwise
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unit_of_measurement: "°"
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accuracy_decimals: 1
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update_interval: 0.1s
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lambda: |-
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if (isnan(id(accel_x).state) || isnan(id(accel_z).state)) {
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return NAN;
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}
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float raw = atan2(-id(accel_x).state, id(accel_z).state) * (180.0 / 3.14159265);
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return raw - id(roll_offset); // Offset wird hier subtrahiert
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filters:
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- sliding_window_moving_average:
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window_size: 8
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send_every: 1
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- exponential_moving_average:
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alpha: 0.2
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globals:
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- id: pitch_offset
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type: float
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restore_value: yes
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initial_value: '0.0'
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- id: roll_offset
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type: float
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restore_value: yes
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initial_value: '0.0'
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# Die Einbaulage liegt im Gerät, nicht in den Apps: Sie beschreibt, wie der
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# Sensor im Fahrzeug sitzt – eine Eigenschaft des Einbaus, nicht des Telefons.
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# Damit sehen iPhone, Uhr und Android dasselbe, ohne sie je einzeln zu
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# bestimmen. Angewandt wird sie weiterhin in den Apps; das Gerät verwahrt sie
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# nur, sonst rechneten ältere Clients die Korrektur ein zweites Mal.
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- id: orientation_version
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type: uint8_t
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restore_value: yes
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initial_value: '0'
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- id: orientation_source
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type: uint8_t
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restore_value: yes
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initial_value: '0'
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- id: orientation_invert_long
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type: bool
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restore_value: yes
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initial_value: 'false'
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- id: orientation_invert_lat
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type: bool
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restore_value: yes
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initial_value: 'false'
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- id: orientation_twist
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type: float
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restore_value: yes
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initial_value: '0.0'
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- id: enable_captive
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type: bool
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restore_value: yes
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initial_value: 'false'
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esp32_ble_server:
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services:
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- uuid: 2a24b789-7aab-4535-af3e-ee76a35cc42d
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advertise: true
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characteristics:
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- id: pitch_ble
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uuid: cad48e28-7fbe-41cf-bae9-d77a6c233424
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description: "Pitch"
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read: true
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value: !lambda |-
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std::vector<unsigned char> v(sizeof(float));
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float val = id(pitch).state;
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memcpy(v.data(), &val, sizeof(float));
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return v;
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- id: roll_ble
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uuid: cad48e28-7fbe-41cf-bae9-d77a6c233425
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description: "Roll"
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read: true
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value: !lambda |-
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std::vector<unsigned char> v(sizeof(float));
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float val = id(roll).state;
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memcpy(v.data(), &val, sizeof(float));
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return v;
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# Die gespeicherten Nullpunkte, zwei Floats. Daran erkennen die Apps,
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# ob überhaupt schon kalibriert wurde.
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- id: offsets_ble
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uuid: cad48e28-7fbe-41cf-bae9-d77a6c233426
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description: "Kalibrier-Offsets"
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read: true
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value: !lambda |-
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std::vector<unsigned char> v(2 * sizeof(float));
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float p = id(pitch_offset);
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float r = id(roll_offset);
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memcpy(v.data(), &p, sizeof(float));
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memcpy(v.data() + sizeof(float), &r, sizeof(float));
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return v;
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# Die Einbaulage, acht Byte:
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#
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# 0 Version, 1 = gültig gesetzt, 0 = nie geschrieben
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# 1 Längsachse: 0 = Pitch des Sensors, 1 = Roll des Sensors
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# 2 längs umgekehrt (0/1)
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# 3 quer umgekehrt (0/1)
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# 4..7 Verdrehung um die Hochachse, float32, Grad
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- id: orientation_ble
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uuid: cad48e28-7fbe-41cf-bae9-d77a6c233428
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description: "Einbaulage"
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read: true
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write: true
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value: !lambda |-
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std::vector<unsigned char> v(8, 0);
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v[0] = id(orientation_version);
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v[1] = id(orientation_source);
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v[2] = id(orientation_invert_long) ? 1 : 0;
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v[3] = id(orientation_invert_lat) ? 1 : 0;
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float t = id(orientation_twist);
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memcpy(v.data() + 4, &t, sizeof(float));
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return v;
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on_write:
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then:
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- lambda: |-
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if (x.size() < 8 || x[0] != 1) {
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ESP_LOGW("vanalign", "Einbaulage verworfen: %d Byte, Version %d",
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(int) x.size(), x.empty() ? -1 : (int) x[0]);
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return;
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}
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float t;
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memcpy(&t, x.data() + 4, sizeof(float));
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if (!std::isfinite(t) || fabsf(t) > 180.0f) {
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ESP_LOGW("vanalign", "Einbaulage verworfen: Verdrehung %.1f", t);
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return;
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}
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id(orientation_version) = 1;
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id(orientation_source) = x[1];
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id(orientation_invert_long) = x[2] != 0;
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id(orientation_invert_lat) = x[3] != 0;
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id(orientation_twist) = t;
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ESP_LOGI("vanalign", "Einbaulage gespeichert: Quelle=%d laengs=%d quer=%d verdreht=%.1f",
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(int) x[1], (int) x[2], (int) x[3], t);
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- id: calib_ble
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uuid: cad48e28-7fbe-41cf-bae9-d77a6c233427
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description: "Kalibriere Neigung"
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write: true
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on_write:
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then:
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- lambda: |-
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bool reset = !x.empty() && (x[0] == 0x00 || x[0] == '0');
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if (reset) {
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id(reset_calibration).execute();
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} else {
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id(calibrate_level).execute();
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}
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#web_server:
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# port: 80
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#ota:
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# platform: web_server
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#wifi:
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# ap:
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# ssid: "VanAlign-Setup"
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# password: "kalibrierung"
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script:
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# Die aktuelle Lage wird zur neuen Null. Knopf und Bluetooth laufen hier
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# zusammen, damit sie nicht auseinanderdriften.
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- id: calibrate_level
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then:
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- lambda: |-
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if (isnan(id(accel_x).state) || isnan(id(accel_y).state) || isnan(id(accel_z).state)) {
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ESP_LOGW("vanalign", "Kalibrierung abgebrochen: keine Sensorwerte");
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return;
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}
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id(pitch_offset) = atan2(id(accel_y).state, sqrt(pow(id(accel_x).state, 2) + pow(id(accel_z).state, 2))) * (180.0 / 3.14159265);
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id(roll_offset) = atan2(-id(accel_x).state, id(accel_z).state) * (180.0 / 3.14159265);
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ESP_LOGI("vanalign", "Kalibriert: pitch_offset=%.2f roll_offset=%.2f", id(pitch_offset), id(roll_offset));
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- id: reset_calibration
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then:
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- lambda: |-
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id(pitch_offset) = 0.0f;
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id(roll_offset) = 0.0f;
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ESP_LOGI("vanalign", "Kalibrierung zurückgesetzt");
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button:
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- platform: template
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name: "Kalibriere Neigung"
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id: calib_button
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on_press:
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- script.execute: calibrate_level
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- platform: template
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name: "Kalibrierung zurücksetzen"
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id: calib_reset_button
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on_press:
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- script.execute: reset_calibration
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- platform: restart
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name: "ESP Restart"
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text_sensor:
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- platform: template
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name: "Firmware Version"
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id: firmware_version
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icon: mdi:tag
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lambda: |-
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return {"v1.0.2-sim"};
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