One EV Battery Reading, Several Versions: An Early Warning for EV Battery Health from the Battery Management System's Own Settings

A battery management system (BMS) in an electric scooter or car measures voltage, current and temperature, and often runs an AI program to tell the health of the battery. Today the rider sees one health number from one reading, with no sign of how firm that number is. This concept note describes a simple check that sits inside the BMS software, on top of any such AI program. Each time the BMS takes a reading, the software also computes the same reading with two to four permitted settings of its own internal parameters. These are not invented changes, so the uncertainty is real. The maker's AI program runs unchanged on every version, and the spread of the answers is measured. A small spread means the health reading is firm. A growing spread means the battery is moving towards a tipping point, such as the knee of capacity fade or overheating, and the weakening pull-back of the battery is what makes the spread grow. The computer then takes a shunting action by itself, without waiting for anyone, for example by reducing the fast-charge current or cutting the charging. The rider sees only a calm state: Steady, Watch or Look closer, with a rough forecast of the days left before the battery needs a check. The note also describes how the method can help find a lead time before an unsafe event. No new sensor or hardware is needed, and the AI program is not changed. No results on real battery data are given in this note. Patent pending. Keywords: EV battery, battery management system, battery health, early warning, tipping point, AI, shunting action, lead time