Critical Slowing Down (CSD) theory predicts that the variance and autocorrelation of stochastic fluctuations in a dynamical system rise as the system approaches a tipping point. This precursor has been demonstrated in ecology, finance, climate, and engineered power systems. Its application to cell-level lithium-ion battery telemetry, under the constraint that no sensor beyond those mandated by current automotive battery monitoring standards may be used, has not been previously published. This preprint outlines a bounded functional J(t), defined as the time-windowed accumulation of cell-current variance weighted by a chemistry-specific sensitivity kernel and raised to a tunable exponent, that maps to a monotonically bounded risk score on the interval zero to one. The general architectural form of the functional and its kernel are described, parameter ranges supported by the published battery-aging literature are identified, and representative applications including downstream actuator outputs in battery management systems, thermal management, fleet maintenance, warranty tracking, insurance analytics, and digital battery passport regulatory data fields are discussed. Specific tuned parameter values, firmware implementations, calibration datasets, and application of this architecture to non-battery substrates are reserved for future work. A limitations and scope section is explicit about what is and is not within the scope of the present disclosure. Correspondence: email only.
Stephen Bonney (Sun,) studied this question.