Erich Blume
0604877db2
## Summary - Renamed all 18 TeslaMate Grafana dashboards to include "Tesla" prefix - Improves organization and discoverability in the dashboard list ## Deployment and Testing - [ ] Sync grafana-config app: `argocd app set grafana-config --revision feature/rename-tesla-dashboards && argocd app sync grafana-config` - [ ] Verify dashboards display with "Tesla" prefix in Grafana 🤖 Generated with [Claude Code](https://claude.com/claude-code) Reviewed-on: https://forge.ops.eblu.me/eblume/blumeops/pulls/68
1262 lines
43 KiB
YAML
1262 lines
43 KiB
YAML
apiVersion: v1
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kind: ConfigMap
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metadata:
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name: grafana-dashboard-teslamate-statistics
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namespace: monitoring
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labels:
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grafana_dashboard: "1"
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annotations:
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grafana_folder: "TeslaMate"
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data:
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teslamate-statistics.json: |
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{
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"annotations": {
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"list": [
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{
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"builtIn": 1,
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"datasource": {
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"type": "grafana",
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"uid": "-- Grafana --"
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},
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"enable": true,
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"hide": true,
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"iconColor": "rgba(0, 211, 255, 1)",
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"name": "Annotations & Alerts",
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"type": "dashboard"
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}
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]
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},
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"editable": true,
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"fiscalYearStartMonth": 0,
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"graphTooltip": 0,
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"links": [
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{
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"icon": "dashboard",
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"tags": [],
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"title": "TeslaMate",
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"type": "link",
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"url": "${base_url:raw}"
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},
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{
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"asDropdown": true,
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"icon": "external link",
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"tags": [
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"tesla"
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],
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"title": "Dashboards",
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"type": "dashboards"
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}
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],
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"panels": [
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{
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"collapsed": false,
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"gridPos": {
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"h": 1,
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"w": 24,
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"x": 0,
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"y": 0
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},
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"id": 4,
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"panels": [],
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"repeat": "car_id",
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"title": "$car_id",
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"type": "row"
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},
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{
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"datasource": {
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"type": "grafana-postgresql-datasource",
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"uid": "TeslaMate"
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},
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"description": "",
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"fieldConfig": {
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"defaults": {
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"custom": {
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"align": "auto",
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"cellOptions": {
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"type": "auto"
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},
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"filterable": false,
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"inspect": false
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},
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"mappings": [],
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"noValue": "--",
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"thresholds": {
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"mode": "absolute",
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"steps": [
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{
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"color": "red",
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"value": 0
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}
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]
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}
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},
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"overrides": [
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{
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"matcher": {
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"id": "byName",
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"options": "Time driven"
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},
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"properties": [
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{
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"id": "unit",
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"value": "dtdurations"
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},
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{
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"id": "decimals",
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"value": 1
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},
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{
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"id": "custom.minWidth",
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"value": 170
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}
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]
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},
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|
{
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|
"matcher": {
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|
"id": "byName",
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|
"options": "Period"
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},
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|
"properties": [
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|
{
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|
"id": "links",
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"value": [
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{
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"targetBlank": true,
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"title": "Trip",
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|
"url": "/d/FkUpJpQZk/trip?from=${__data.fields.date_from}&to=${__data.fields.date_to}&var-car_id=$car_id"
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}
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|
]
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|
},
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{
|
|
"id": "custom.minWidth",
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|
"value": 195
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|
}
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]
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|
},
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|
{
|
|
"matcher": {
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|
"id": "byName",
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"options": "Driving Efficiency"
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|
},
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|
"properties": [
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|
{
|
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"id": "unit",
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|
"value": "percentunit"
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|
},
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{
|
|
"id": "thresholds",
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"value": {
|
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"mode": "absolute",
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"steps": [
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{
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|
"color": "super-light-orange",
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"value": 0
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},
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{
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|
"color": "light-orange",
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"value": 0.65
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},
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{
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"color": "light-green",
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"value": 0.99
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}
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]
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}
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},
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|
{
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|
"id": "max",
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"value": 1.15
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},
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{
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|
"id": "min",
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"value": 0
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},
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{
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"id": "custom.cellOptions",
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"value": {
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|
"mode": "lcd",
|
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"type": "gauge"
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}
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|
},
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{
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"id": "decimals"
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}
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]
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},
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|
{
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|
"matcher": {
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|
"id": "byName",
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|
"options": "Energy used"
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|
},
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|
"properties": [
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|
{
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|
"id": "decimals",
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|
"value": 1
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|
},
|
|
{
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|
"id": "links",
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|
"value": [
|
|
{
|
|
"targetBlank": true,
|
|
"title": "Charging stats",
|
|
"url": "/d/-pkIkhmRz/charging-stats?from=${__data.fields.date_from}&to=${__data.fields.date_to}&var-car_id=$car_id"
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|
}
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|
]
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|
},
|
|
{
|
|
"id": "unit",
|
|
"value": "kwatth"
|
|
},
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|
{
|
|
"id": "custom.minWidth",
|
|
"value": 120
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|
}
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|
]
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|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "Ø Energy used / Charge"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "unit",
|
|
"value": "kwatth"
|
|
},
|
|
{
|
|
"id": "decimals",
|
|
"value": 1
|
|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 190
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|
}
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]
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|
},
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|
{
|
|
"matcher": {
|
|
"id": "byName",
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|
"options": "Costs"
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|
},
|
|
"properties": [
|
|
{
|
|
"id": "decimals",
|
|
"value": 2
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|
},
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|
{
|
|
"id": "custom.minWidth",
|
|
"value": 75
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|
}
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]
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|
},
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|
{
|
|
"matcher": {
|
|
"id": "byName",
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|
"options": "# of Charges"
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|
},
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|
"properties": [
|
|
{
|
|
"id": "links",
|
|
"value": [
|
|
{
|
|
"targetBlank": true,
|
|
"title": "Charges",
|
|
"url": "/d/TSmNYvRRk/charges?from=${__data.fields.date_from}&to=${__data.fields.date_to}&var-car_id=$car_id"
|
|
}
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|
]
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|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 110
|
|
}
|
|
]
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|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "# of Drives"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "links",
|
|
"value": [
|
|
{
|
|
"targetBlank": true,
|
|
"title": "Drives",
|
|
"url": "/d/Y8upc6ZRk/drives?from=${__data.fields.date_from}&to=${__data.fields.date_to}&var-car_id=$car_id"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 95
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byRegexp",
|
|
"options": "/sum_distance_km/"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "unit",
|
|
"value": "km"
|
|
},
|
|
{
|
|
"id": "displayName",
|
|
"value": "Distance"
|
|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 100
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byRegexp",
|
|
"options": "/avg_outside_temp_c/"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "unit",
|
|
"value": "celsius"
|
|
},
|
|
{
|
|
"id": "displayName",
|
|
"value": "Ø Temp"
|
|
},
|
|
{
|
|
"id": "thresholds",
|
|
"value": {
|
|
"mode": "absolute",
|
|
"steps": [
|
|
{
|
|
"color": "super-light-blue",
|
|
"value": 0
|
|
},
|
|
{
|
|
"color": "super-light-green",
|
|
"value": 10
|
|
},
|
|
{
|
|
"color": "super-light-red",
|
|
"value": 20
|
|
}
|
|
]
|
|
}
|
|
},
|
|
{
|
|
"id": "custom.cellOptions",
|
|
"value": {
|
|
"type": "color-text"
|
|
}
|
|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 80
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byRegexp",
|
|
"options": "/sum_distance_mi/"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "displayName",
|
|
"value": "Distance"
|
|
},
|
|
{
|
|
"id": "unit",
|
|
"value": "mi"
|
|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 100
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byRegexp",
|
|
"options": "/consumption_net_mi/"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "unit",
|
|
"value": "Wh/mi"
|
|
},
|
|
{
|
|
"id": "custom.width",
|
|
"value": 170
|
|
},
|
|
{
|
|
"id": "displayName",
|
|
"value": "Ø Consumption (net)"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byRegexp",
|
|
"options": "/consumption_gross_mi/"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "displayName",
|
|
"value": "Ø Consumption (gross)"
|
|
},
|
|
{
|
|
"id": "unit",
|
|
"value": "Wh/mi"
|
|
},
|
|
{
|
|
"id": "custom.width",
|
|
"value": 190
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byRegexp",
|
|
"options": "/consumption_net_km/"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "displayName",
|
|
"value": "Ø Consumption (net)"
|
|
},
|
|
{
|
|
"id": "unit",
|
|
"value": "Wh/km"
|
|
},
|
|
{
|
|
"id": "custom.width",
|
|
"value": 170
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byRegexp",
|
|
"options": "/consumption_gross_km/"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "displayName",
|
|
"value": "Ø Consumption (gross)"
|
|
},
|
|
{
|
|
"id": "unit",
|
|
"value": "Wh/km"
|
|
},
|
|
{
|
|
"id": "custom.width",
|
|
"value": 190
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byRegexp",
|
|
"options": "/avg_outside_temp_f/"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "displayName",
|
|
"value": "Ø Temp"
|
|
},
|
|
{
|
|
"id": "unit",
|
|
"value": "fahrenheit"
|
|
},
|
|
{
|
|
"id": "custom.cellOptions",
|
|
"value": {
|
|
"type": "color-text"
|
|
}
|
|
},
|
|
{
|
|
"id": "thresholds",
|
|
"value": {
|
|
"mode": "absolute",
|
|
"steps": [
|
|
{
|
|
"color": "super-light-blue",
|
|
"value": 0
|
|
},
|
|
{
|
|
"color": "super-light-green",
|
|
"value": 50
|
|
},
|
|
{
|
|
"color": "super-light-red",
|
|
"value": 68
|
|
}
|
|
]
|
|
}
|
|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 80
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "date_from"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "custom.hidden",
|
|
"value": true
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "date_to"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "custom.hidden",
|
|
"value": true
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "Ø Cost / kWh"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "decimals",
|
|
"value": 2
|
|
},
|
|
{
|
|
"id": "mappings",
|
|
"value": [
|
|
{
|
|
"options": {
|
|
"NaN": {
|
|
"index": 0,
|
|
"text": "--"
|
|
}
|
|
},
|
|
"type": "value"
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 115
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "Ø Cost / 100 km"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "decimals",
|
|
"value": 2
|
|
},
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 135
|
|
},
|
|
{
|
|
"id": "mappings",
|
|
"value": [
|
|
{
|
|
"options": {
|
|
"NaN": {
|
|
"index": 0,
|
|
"text": "--"
|
|
}
|
|
},
|
|
"type": "value"
|
|
}
|
|
]
|
|
}
|
|
]
|
|
},
|
|
{
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "Consumption OH"
|
|
},
|
|
"properties": [
|
|
{
|
|
"id": "custom.minWidth",
|
|
"value": 140
|
|
},
|
|
{
|
|
"id": "unit",
|
|
"value": "percentunit"
|
|
},
|
|
{
|
|
"id": "decimals",
|
|
"value": 0
|
|
},
|
|
{
|
|
"id": "mappings",
|
|
"value": [
|
|
{
|
|
"options": {
|
|
"NaN": {
|
|
"index": 0,
|
|
"text": "--"
|
|
}
|
|
},
|
|
"type": "value"
|
|
}
|
|
]
|
|
}
|
|
]
|
|
}
|
|
]
|
|
},
|
|
"gridPos": {
|
|
"h": 18,
|
|
"w": 24,
|
|
"x": 0,
|
|
"y": 1
|
|
},
|
|
"id": 2,
|
|
"maxPerRow": 2,
|
|
"options": {
|
|
"cellHeight": "sm",
|
|
"footer": {
|
|
"countRows": false,
|
|
"fields": "",
|
|
"reducer": [
|
|
"sum"
|
|
],
|
|
"show": false
|
|
},
|
|
"frameIndex": 1,
|
|
"showHeader": true,
|
|
"sortBy": [
|
|
{
|
|
"desc": true,
|
|
"displayName": "Starting at"
|
|
}
|
|
]
|
|
},
|
|
"pluginVersion": "12.1.1",
|
|
"targets": [
|
|
{
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"editorMode": "code",
|
|
"format": "table",
|
|
"rawQuery": true,
|
|
"rawSql": "WITH data AS (\nSELECT\n duration_min > 1 AND\n distance > 1 AND\n ( \n start_position.usable_battery_level IS NULL OR\n (end_position.battery_level - end_position.usable_battery_level) = 0 \n ) AS is_sufficiently_precise,\n start_${preferred_range}_range_km - end_${preferred_range}_range_km AS range_diff,\n date_trunc('$period', timezone('UTC', start_date), '$__timezone') as date,\n drives.*\nFROM drives\n LEFT JOIN positions start_position ON start_position_id = start_position.id\n LEFT JOIN positions end_position ON end_position_id = end_position.id)\nSELECT\n EXTRACT(EPOCH FROM date)*1000 AS date_from,\n EXTRACT(EPOCH FROM date + interval '1 $period')*1000 AS date_to,\n CASE '$period'\n WHEN 'month' THEN to_char(timezone('$__timezone', date), 'YYYY Month')\n WHEN 'year' THEN to_char(timezone('$__timezone', date), 'YYYY')\n WHEN 'week' THEN 'week ' || to_char(timezone('$__timezone', date), 'WW') || ' starting ' || to_char(timezone('$__timezone', date), 'YYYY-MM-DD')\n ELSE to_char(timezone('$__timezone', date), 'YYYY-MM-DD')\n END AS display,\n date,\n sum(duration_min)*60 AS sum_duration_h, \n convert_km(max(end_km)::numeric - min(start_km)::numeric, '$length_unit') AS sum_distance_$length_unit,\n convert_celsius(avg(outside_temp_avg), '$temp_unit') AS avg_outside_temp_$temp_unit,\n count(*) AS cnt,\n case when sum(range_diff) > 0 then sum(distance)/sum(range_diff) else null end AS efficiency\nFROM data WHERE\n car_id = $car_id AND\n $__timeFilter(start_date)\nGROUP BY date",
|
|
"refId": "A",
|
|
"sql": {
|
|
"columns": [
|
|
{
|
|
"parameters": [],
|
|
"type": "function"
|
|
}
|
|
],
|
|
"groupBy": [
|
|
{
|
|
"property": {
|
|
"type": "string"
|
|
},
|
|
"type": "groupBy"
|
|
}
|
|
],
|
|
"limit": 50
|
|
}
|
|
},
|
|
{
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"editorMode": "code",
|
|
"format": "table",
|
|
"rawQuery": true,
|
|
"rawSql": "WITH data AS (\n SELECT\n charging_processes.*,\n \tdate_trunc('$period', timezone('UTC', start_date), '$__timezone') as date\n FROM charging_processes)\nSELECT\n EXTRACT(EPOCH FROM date)*1000 AS date_from,\n EXTRACT(EPOCH FROM date + interval '1 $period')*1000 AS date_to,\n CASE '$period'\n WHEN 'month' THEN to_char(timezone('$__timezone', date), 'YYYY Month')\n WHEN 'year' THEN to_char(timezone('$__timezone', date), 'YYYY')\n WHEN 'week' THEN 'week ' || to_char(timezone('$__timezone', date), 'WW') || ' starting ' || to_char(timezone('$__timezone', date), 'YYYY-MM-DD')\n ELSE to_char(timezone('$__timezone', date), 'YYYY-MM-DD')\n END AS display,\n date,\n sum(greatest(charge_energy_added,charge_energy_used)) AS sum_energy_used_kwh,\n sum(charge_energy_added) as sum_energy_added_kwh,\n sum(greatest(charge_energy_added,charge_energy_used)) / count(*) AS avg_energy_charged_kwh,\n sum(cost) AS cost_charges,\n count(*) AS cnt_charges\nFROM data WHERE\n car_id = $car_id AND\n $__timeFilter(start_date) AND\n (charge_energy_added IS NULL OR charge_energy_added > 0.1)\nGROUP BY date",
|
|
"refId": "B",
|
|
"sql": {
|
|
"columns": [
|
|
{
|
|
"parameters": [],
|
|
"type": "function"
|
|
}
|
|
],
|
|
"groupBy": [
|
|
{
|
|
"property": {
|
|
"type": "string"
|
|
},
|
|
"type": "groupBy"
|
|
}
|
|
],
|
|
"limit": 50
|
|
}
|
|
},
|
|
{
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"editorMode": "code",
|
|
"format": "table",
|
|
"rawQuery": true,
|
|
"rawSql": "WITH data AS (\n SELECT\n drives.*,\n date_trunc('$period', timezone('UTC', start_date), '$__timezone') as date\n FROM drives)\nSELECT\n EXTRACT(EPOCH FROM date)*1000 AS date_from,\n EXTRACT(EPOCH FROM date + interval '1 $period')*1000 AS date_to,\n CASE '$period'\n WHEN 'month' THEN to_char(timezone('$__timezone', date), 'YYYY Month')\n WHEN 'year' THEN to_char(timezone('$__timezone', date), 'YYYY')\n WHEN 'week' THEN 'week ' || to_char(timezone('$__timezone', date), 'WW') || ' starting ' || to_char(timezone('$__timezone', date), 'YYYY-MM-DD')\n ELSE to_char(timezone('$__timezone', date), 'YYYY-MM-DD')\n END AS display,\n date,\n sum((start_${preferred_range}_range_km - end_${preferred_range}_range_km) * car.efficiency * 1000) / \n convert_km(sum(distance)::numeric, '$length_unit') as consumption_net_$length_unit\nFROM data\nJOIN cars car ON car.id = car_id\nWHERE\n car_id = $car_id AND\n $__timeFilter(start_date)\nGROUP BY date",
|
|
"refId": "C",
|
|
"sql": {
|
|
"columns": [
|
|
{
|
|
"parameters": [],
|
|
"type": "function"
|
|
}
|
|
],
|
|
"groupBy": [
|
|
{
|
|
"property": {
|
|
"type": "string"
|
|
},
|
|
"type": "groupBy"
|
|
}
|
|
],
|
|
"limit": 50
|
|
}
|
|
},
|
|
{
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"editorMode": "code",
|
|
"format": "table",
|
|
"rawQuery": true,
|
|
"rawSql": "-- Query shared between Charging Stats, Statistics & Trip Dashboards (with minor changes) - ensure to modify in all places when necessary\n\nwith drives_start_event as (\n\n select\n 'drive_start' as event, start_date as date, start_${preferred_range}_range_km as range, start_km as odometer, car_id\n from drives\n where car_id = $car_id and $__timeFilter(start_date) and 0 = $high_precision\n\n),\n\ndrives_end_event as (\n\n select\n 'drive_end' as event, end_date as date, end_${preferred_range}_range_km as range, end_km as odometer, car_id\n from drives\n where car_id = $car_id and $__timeFilter(start_date) and 0 = $high_precision\n\n),\n\ncharging_processes_start_event as (\n\n select\n 'charging_process_start' as event, start_date as date, start_${preferred_range}_range_km as range, p.odometer, cp.car_id\n from charging_processes cp\n inner join positions p on cp.position_id = p.id\n where cp.car_id = $car_id and $__timeFilter(start_date) and 0 = $high_precision\n\n),\n\ncharging_processes_end_event as (\n\n select\n 'charging_process_end' as event, end_date as date, end_${preferred_range}_range_km as range, p.odometer, cp.car_id\n from charging_processes cp\n inner join positions p on cp.position_id = p.id\n where cp.car_id = $car_id and $__timeFilter(start_date) and 0 = $high_precision\n\n),\n\npositions as (\n\n select\n case\n when drive_id is not null and lead(drive_id) over w is not null then 'drive_start'\n else 'something'\n end as event,\n date, ${preferred_range}_battery_range_km as range, p.odometer, p.car_id\n from positions p\n where ideal_battery_range_km is not null and car_id = $car_id and 1 = $high_precision\n and (drive_id in (select id from drives where $__timeFilter(start_date)) or drive_id is null and $__timeFilter(date))\n window w as (order by date)\n\n),\n\ncombined as (\n\n select * from drives_start_event\n union all\n select * from drives_end_event\n union all\n select * from charging_processes_start_event\n union all\n select * from charging_processes_end_event\n union all\n select * from positions\n\n),\n\nfinal as (\n\n select\n car_id,\n date_trunc('$period', timezone('UTC', date), '$__timezone') as date,\n lead(odometer) over w - odometer as distance,\n case when event != 'drive_start' then greatest(range - lead(range) over w, 0) else range - lead(range) over w end as range_loss\n from combined\n window w as (order by date asc)\n\n)\n\nselect\n EXTRACT(EPOCH FROM date)*1000 AS date_from,\n EXTRACT(EPOCH FROM date + interval '1 $period')*1000 AS date_to,\n CASE '$period'\n WHEN 'month' THEN to_char(timezone('$__timezone', date), 'YYYY Month')\n WHEN 'year' THEN to_char(timezone('$__timezone', date), 'YYYY')\n WHEN 'week' THEN 'week ' || to_char(timezone('$__timezone', date), 'WW') || ' starting ' || to_char(timezone('$__timezone', date), 'YYYY-MM-DD')\n ELSE to_char(timezone('$__timezone', date), 'YYYY-MM-DD')\n END AS display,\n date,\n (sum(range_loss) * c.efficiency * 1000) / nullif(convert_km(sum(distance)::numeric, '$length_unit'), 0) as consumption_gross_$length_unit\nfrom final\n inner join cars c on car_id = c.id\ngroup by 1, 2, 3, 4, c.efficiency",
|
|
"refId": "D",
|
|
"sql": {
|
|
"columns": [
|
|
{
|
|
"parameters": [],
|
|
"type": "function"
|
|
}
|
|
],
|
|
"groupBy": [
|
|
{
|
|
"property": {
|
|
"type": "string"
|
|
},
|
|
"type": "groupBy"
|
|
}
|
|
],
|
|
"limit": 50
|
|
}
|
|
}
|
|
],
|
|
"title": "per ${period}",
|
|
"transformations": [
|
|
{
|
|
"id": "merge",
|
|
"options": {}
|
|
},
|
|
{
|
|
"id": "seriesToColumns",
|
|
"options": {
|
|
"byField": "date"
|
|
}
|
|
},
|
|
{
|
|
"id": "sortBy",
|
|
"options": {
|
|
"fields": {},
|
|
"sort": [
|
|
{
|
|
"desc": true,
|
|
"field": "date"
|
|
}
|
|
]
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "avg_cost_kwh",
|
|
"binary": {
|
|
"left": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "cost_charges"
|
|
}
|
|
},
|
|
"operator": "/",
|
|
"right": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "sum_energy_used_kwh"
|
|
}
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "avg_cost_added_kwh",
|
|
"binary": {
|
|
"left": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "cost_charges"
|
|
}
|
|
},
|
|
"operator": "/",
|
|
"right": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "sum_energy_added_kwh"
|
|
}
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "cost_per_1000km",
|
|
"binary": {
|
|
"left": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "consumption_gross_km"
|
|
}
|
|
},
|
|
"operator": "*",
|
|
"right": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "avg_cost_added_kwh"
|
|
}
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "cost_per_1000mi",
|
|
"binary": {
|
|
"left": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "consumption_gross_mi"
|
|
}
|
|
},
|
|
"operator": "*",
|
|
"right": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "avg_cost_added_kwh"
|
|
}
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "avg_cost_km",
|
|
"binary": {
|
|
"left": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "cost_per_1000km"
|
|
}
|
|
},
|
|
"operator": "/",
|
|
"right": {
|
|
"fixed": "10"
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "avg_cost_mi",
|
|
"binary": {
|
|
"left": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "cost_per_1000mi"
|
|
}
|
|
},
|
|
"operator": "/",
|
|
"right": {
|
|
"fixed": "10"
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "overhead_pct_km_temp",
|
|
"binary": {
|
|
"left": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "consumption_net_km"
|
|
}
|
|
},
|
|
"operator": "/",
|
|
"right": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "consumption_gross_km"
|
|
}
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "overhead_pct_km",
|
|
"binary": {
|
|
"left": {
|
|
"fixed": "1"
|
|
},
|
|
"operator": "-",
|
|
"right": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "overhead_pct_km_temp"
|
|
}
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "overhead_pct_mi_temp",
|
|
"binary": {
|
|
"left": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "consumption_net_mi"
|
|
}
|
|
},
|
|
"operator": "/",
|
|
"right": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "consumption_gross_mi"
|
|
}
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "calculateField",
|
|
"options": {
|
|
"alias": "overhead_pct_mi",
|
|
"binary": {
|
|
"left": {
|
|
"fixed": "1"
|
|
},
|
|
"operator": "-",
|
|
"right": {
|
|
"matcher": {
|
|
"id": "byName",
|
|
"options": "overhead_pct_mi_temp"
|
|
}
|
|
}
|
|
},
|
|
"mode": "binary",
|
|
"reduce": {
|
|
"reducer": "sum"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"id": "organize",
|
|
"options": {
|
|
"excludeByName": {
|
|
"avg_cost_added_kwh": true,
|
|
"cost_per_1000km": true,
|
|
"cost_per_1000mi": true,
|
|
"date": true,
|
|
"overhead_pct_km_temp": true,
|
|
"overhead_pct_mi_temp": true,
|
|
"sum_energy_added_kwh": true
|
|
},
|
|
"includeByName": {},
|
|
"indexByName": {
|
|
"avg_cost_km": 12,
|
|
"avg_cost_kwh": 11,
|
|
"avg_cost_mi": 12,
|
|
"avg_energy_charged_kwh": 8,
|
|
"avg_outside_temp_c": 4,
|
|
"avg_outside_temp_f": 4,
|
|
"cnt": 5,
|
|
"cnt_charges": 10,
|
|
"consumption_gross_km": 14,
|
|
"consumption_gross_mi": 14,
|
|
"consumption_net_km": 13,
|
|
"consumption_net_mi": 13,
|
|
"cost_charges": 9,
|
|
"date": 1,
|
|
"date_from": 15,
|
|
"date_to": 16,
|
|
"display": 0,
|
|
"efficiency": 6,
|
|
"overhead_pct_km": 17,
|
|
"overhead_pct_mi": 17,
|
|
"sum_distance_km": 3,
|
|
"sum_distance_mi": 3,
|
|
"sum_duration_h": 2,
|
|
"sum_energy_used_kwh": 7
|
|
},
|
|
"renameByName": {
|
|
"avg_cost_km": "Ø Cost / 100 km",
|
|
"avg_cost_kwh": "Ø Cost / kWh",
|
|
"avg_cost_mi": "Ø Cost / 100 mi",
|
|
"avg_energy_charged_kwh": "Ø Energy used / Charge",
|
|
"avg_outside_temp_c": "",
|
|
"avg_outside_temp_f": "",
|
|
"cnt": "# of Drives",
|
|
"cnt_charges": "# of Charges",
|
|
"consumption_gross_km": "",
|
|
"consumption_gross_mi": "",
|
|
"consumption_net_km": "",
|
|
"consumption_net_mi": "",
|
|
"cost_charges": "Costs",
|
|
"date": "",
|
|
"date_from": "",
|
|
"date_to": "",
|
|
"display": "Period",
|
|
"efficiency": "Driving Efficiency",
|
|
"overhead_pct_km": "Consumption OH",
|
|
"overhead_pct_mi": "Consumption OH",
|
|
"sum_distance_km": "",
|
|
"sum_distance_mi": "",
|
|
"sum_duration_h": "Time driven",
|
|
"sum_energy_used_kwh": "Energy used"
|
|
}
|
|
}
|
|
}
|
|
],
|
|
"type": "table"
|
|
}
|
|
],
|
|
"preload": false,
|
|
"refresh": "",
|
|
"schemaVersion": 41,
|
|
"tags": [
|
|
"tesla"
|
|
],
|
|
"templating": {
|
|
"list": [
|
|
{
|
|
"current": {},
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"definition": "SELECT\n id as __value,\n CASE WHEN COUNT(id) OVER (PARTITION BY name) > 1 AND name IS NOT NULL THEN CONCAT(name, ' - ', RIGHT(vin, 6)) ELSE COALESCE(name, CONCAT('VIN ', vin)) end as __text \nFROM cars\nORDER BY display_priority ASC, name ASC, vin ASC;",
|
|
"hide": 2,
|
|
"includeAll": true,
|
|
"label": "Car",
|
|
"name": "car_id",
|
|
"options": [],
|
|
"query": "SELECT\n id as __value,\n CASE WHEN COUNT(id) OVER (PARTITION BY name) > 1 AND name IS NOT NULL THEN CONCAT(name, ' - ', RIGHT(vin, 6)) ELSE COALESCE(name, CONCAT('VIN ', vin)) end as __text \nFROM cars\nORDER BY display_priority ASC, name ASC, vin ASC;",
|
|
"refresh": 1,
|
|
"regex": "",
|
|
"type": "query"
|
|
},
|
|
{
|
|
"current": {},
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"definition": "select unit_of_length from settings limit 1;",
|
|
"hide": 2,
|
|
"includeAll": false,
|
|
"label": "length unit",
|
|
"name": "length_unit",
|
|
"options": [],
|
|
"query": "select unit_of_length from settings limit 1;",
|
|
"refresh": 1,
|
|
"regex": "",
|
|
"type": "query"
|
|
},
|
|
{
|
|
"current": {},
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"definition": "select unit_of_temperature from settings limit 1;",
|
|
"hide": 2,
|
|
"includeAll": false,
|
|
"label": "temperature unit",
|
|
"name": "temp_unit",
|
|
"options": [],
|
|
"query": "select unit_of_temperature from settings limit 1;",
|
|
"refresh": 1,
|
|
"regex": "",
|
|
"type": "query"
|
|
},
|
|
{
|
|
"current": {
|
|
"text": "month",
|
|
"value": "month"
|
|
},
|
|
"includeAll": false,
|
|
"label": "Period",
|
|
"name": "period",
|
|
"options": [
|
|
{
|
|
"selected": false,
|
|
"text": "day",
|
|
"value": "day"
|
|
},
|
|
{
|
|
"selected": false,
|
|
"text": "week",
|
|
"value": "week"
|
|
},
|
|
{
|
|
"selected": true,
|
|
"text": "month",
|
|
"value": "month"
|
|
},
|
|
{
|
|
"selected": false,
|
|
"text": "year",
|
|
"value": "year"
|
|
}
|
|
],
|
|
"query": "day,week,month,year",
|
|
"type": "custom"
|
|
},
|
|
{
|
|
"current": {},
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"definition": "select preferred_range from settings limit 1;",
|
|
"hide": 2,
|
|
"includeAll": false,
|
|
"name": "preferred_range",
|
|
"options": [],
|
|
"query": "select preferred_range from settings limit 1;",
|
|
"refresh": 1,
|
|
"regex": "",
|
|
"type": "query"
|
|
},
|
|
{
|
|
"current": {},
|
|
"datasource": {
|
|
"type": "grafana-postgresql-datasource",
|
|
"uid": "TeslaMate"
|
|
},
|
|
"definition": "select base_url from settings limit 1;",
|
|
"hide": 2,
|
|
"includeAll": false,
|
|
"name": "base_url",
|
|
"options": [],
|
|
"query": "select base_url from settings limit 1;",
|
|
"refresh": 1,
|
|
"regex": "",
|
|
"type": "query"
|
|
},
|
|
{
|
|
"current": {
|
|
"text": "no",
|
|
"value": "0"
|
|
},
|
|
"description": "When enabled \"Ø Consumption (gross)\" will be calculated via Positions instead of Charging Processes and Drives.\n\nWhile being more accurate (especially for shorter periods) this will be slow on slow hardware!",
|
|
"includeAll": false,
|
|
"label": "High Precision",
|
|
"name": "high_precision",
|
|
"options": [
|
|
{
|
|
"selected": true,
|
|
"text": "no",
|
|
"value": "0"
|
|
},
|
|
{
|
|
"selected": false,
|
|
"text": "yes",
|
|
"value": "1"
|
|
}
|
|
],
|
|
"query": "no : 0, yes : 1",
|
|
"type": "custom"
|
|
}
|
|
]
|
|
},
|
|
"time": {
|
|
"from": "now-10y",
|
|
"to": "now"
|
|
},
|
|
"timepicker": {},
|
|
"timezone": "",
|
|
"title": "Tesla Statistics",
|
|
"uid": "1EZnXszMk",
|
|
"version": 1
|
|
}
|