{
  "node": {
    "id": "term:fuzzy-logic",
    "type": "Term",
    "label": "Fuzzy logic",
    "properties": {
      "id": "fuzzy-logic",
      "name": "Fuzzy logic",
      "aka": [
        "fuzzy inference",
        "fuzzy controller"
      ],
      "section": "topic-data",
      "definition": "Reasoning with degrees of truth between 0 and 1, so that a temperature can be partly ‘warm’ and partly ‘hot’, combined through if–then rules. It has been applied to SOC and SOH estimation and to charge control because it encodes expert knowledge without a precise model, though its rules and membership functions still need tuning on test data.",
      "related": [
        "state-of-charge",
        "state-of-health",
        "kalman-filter",
        "pid-controller"
      ],
      "url": "https://lemonergy.com/learn/glossary/fuzzy-logic/",
      "mentions": []
    }
  },
  "edges": [
    {
      "id": "edge:5322",
      "source": "term:fuzzy-logic",
      "target": "topic:topic-data",
      "type": "belongsTo",
      "properties": {
        "sourceFile": "terms.json"
      }
    },
    {
      "id": "edge:5323",
      "source": "term:fuzzy-logic",
      "target": "term:state-of-charge",
      "type": "relatedTo",
      "properties": {
        "sourceFile": "terms.json",
        "meaning": "Related context; not a causal claim"
      }
    },
    {
      "id": "edge:5324",
      "source": "term:fuzzy-logic",
      "target": "term:state-of-health",
      "type": "relatedTo",
      "properties": {
        "sourceFile": "terms.json",
        "meaning": "Related context; not a causal claim"
      }
    },
    {
      "id": "edge:5325",
      "source": "term:fuzzy-logic",
      "target": "term:kalman-filter",
      "type": "relatedTo",
      "properties": {
        "sourceFile": "terms.json",
        "meaning": "Related context; not a causal claim"
      }
    },
    {
      "id": "edge:5326",
      "source": "term:fuzzy-logic",
      "target": "term:pid-controller",
      "type": "relatedTo",
      "properties": {
        "sourceFile": "terms.json",
        "meaning": "Related context; not a causal claim"
      }
    }
  ],
  "neighbors": [
    {
      "id": "topic:topic-data",
      "type": "Topic",
      "label": "Data, communication and electronics",
      "properties": {
        "id": "topic-data",
        "name": "Data, communication and electronics",
        "lede": "The control units, chips, protocols and file formats through which a battery is measured, controlled and logged.",
        "context": "Separate quantities from encoding and transport.",
        "example": "2500 in a log might mean 25.00 °C, 2.5 V or raw counts. Units and scale must accompany the value.",
        "lesson_url": "https://lemonergy.com/learn/fundamentals/battery-basics/",
        "lesson_label": "Open battery basics"
      }
    },
    {
      "id": "term:state-of-charge",
      "type": "Term",
      "label": "State of charge",
      "properties": {
        "id": "state-of-charge",
        "name": "State of charge",
        "abbr": "SOC",
        "section": "topic-state",
        "definition": "How full a cell is, as a fraction of its available capacity. State of charge, like temperature, affects how fast a stored cell ages.",
        "unit": "%",
        "related": [
          "depth-of-discharge",
          "ocv-soc-curve",
          "coulomb-counting",
          "state-of-health",
          "bms"
        ],
        "lesson": "fundamentals/battery-aging/#storage-soc",
        "example": {
          "title": "Interpret a charge inventory",
          "text": "If available capacity is 5 Ah and 3 Ah remains by the chosen estimator, SOC is 60%. A different estimate of available capacity changes this percentage, so compare SOC values only with the capacity convention recorded."
        },
        "url": "https://lemonergy.com/learn/glossary/state-of-charge/",
        "mentions": [
          "usable-capacity"
        ]
      }
    },
    {
      "id": "term:state-of-health",
      "type": "Term",
      "label": "State of health",
      "properties": {
        "id": "state-of-health",
        "name": "State of health",
        "abbr": "SOH",
        "section": "topic-state",
        "definition": "A summary of how far a cell has aged, often expressed through remaining capacity or increased resistance compared with when it was new. By convention a cell has reached end of life at 80 % of its rated capacity.",
        "unit": "%",
        "related": [
          "capacity-fade",
          "impedance-rise",
          "end-of-life",
          "remaining-useful-life",
          "state-of-charge",
          "state-of-certified-energy"
        ],
        "lesson": "fundamentals/capacity-and-c-rate/#real-cells",
        "url": "https://lemonergy.com/learn/glossary/state-of-health/",
        "mentions": [
          "nominal-capacity"
        ]
      }
    },
    {
      "id": "term:kalman-filter",
      "type": "Term",
      "label": "Kalman filter",
      "properties": {
        "id": "kalman-filter",
        "name": "Kalman filter",
        "section": "topic-state",
        "definition": "A recursive estimator that blends a model prediction with noisy measurements according to how much each is trusted. In a BMS an extended Kalman filter combines coulomb counting with a voltage model to track SOC and sometimes resistance.",
        "related": [
          "coulomb-counting",
          "equivalent-circuit-model",
          "state-of-charge",
          "bms",
          "fuzzy-logic",
          "data-driven-soc-estimation"
        ],
        "url": "https://lemonergy.com/learn/glossary/kalman-filter/",
        "mentions": [
          "coulomb"
        ]
      }
    },
    {
      "id": "term:pid-controller",
      "type": "Term",
      "label": "PID controller",
      "properties": {
        "id": "pid-controller",
        "name": "PID controller",
        "abbr": "PID",
        "aka": [
          "proportional–integral–derivative controller",
          "PI controller"
        ],
        "section": "topic-data",
        "definition": "A feedback controller whose output is a weighted sum of the present error, its accumulated integral and its rate of change. It is the workhorse of battery systems — holding coolant temperature with a pump or compressor, regulating charger current and voltage — and often runs as PI only, without the derivative term.",
        "formula": "u = K_p·e + K_i·∫e dt + K_d·de/dt",
        "related": [
          "feedback-feedforward-control",
          "gain-scheduling",
          "thermal-management",
          "plant-model",
          "model-predictive-control"
        ],
        "example": {
          "title": "Separate three controller contributions",
          "text": "For an illustrative error e = 2, accumulated error 3 s and error slope −0.5/s, gains Kp = 1, Ki = 0.5/s and Kd = 0.2 s give u = 2 + 1.5 − 0.1 = 3.4. Output limits and anti-windup are separate design choices."
        },
        "url": "https://lemonergy.com/learn/glossary/pid-controller/",
        "mentions": [
          "charger",
          "refrigerant-loop"
        ]
      }
    }
  ]
}