Electrical Testing TRIZ Cases

A remote server predicts remaining battery life from temperature and usage events, improving accuracy while avoiding power-hungry direct measurement.

A shared battery measurement component keeps power level displays consistent across dual operating systems during system switching.

Curvature extracted from voltage-capacity data reveals battery cell degradation in plateau regions where differential voltage peaks are hard to detect.

Time-series voltage analysis uses moving averages, standard deviation, and current-change masking to detect abnormal battery cells with fewer false positives.

Combining pulse-segment fitting with rest-segment optimization improves battery model parameter accuracy and open-circuit voltage estimation.

Tracks AC input voltage change ratios across monitoring periods to detect Forsmark effects early and protect nuclear-class electrical equipment.

Continuous checker-signal monitoring identifies flip-flop or checker faults and corrects bit toggles within one clock cycle.

Cycle-based correction profiles and normalization values reveal long-term battery trends and help distinguish lithium plating from normal states.

Charging voltage difference trends and cycle data quantify battery swelling risk early, avoiding extra sensors and binary-only detection.

Pre-trained AI predicts discharge voltage curves from in-use battery data to check SOH faster without full charge-discharge tests.

Differential profile peak comparison estimates battery degradation quickly without full charging, improving accuracy and battery usage control.

A recursive filter updates battery capacity from SOC change and charge throughput, limiting Coulomb-counting drift without invasive testing.

Predicted battery degradation guides electric work machine assignment by workload, helping suppress battery wear and extend service life.

AI models infer discharge curves from charging data to estimate battery SOH faster, avoiding long full charge-discharge tests.

A time-domain RFID tag couples PD pulses with asset ID, improving localization and lowering reader complexity in multi-asset electrical systems.

A measurement unit wakes the sleeping battery controller only on abnormal state changes, improving thermal runaway detection while limiting power use.

A shadow access port reuses JTAG TAP signals on the TCK falling edge to add debug, trace, and programming without redesign.

A Gaussian-process model separates average degradation from time-varying device variability to improve state-of-health and life prediction.

Automated relay switching measures battery voltages to calculate resistance and detect intermittent or balanced grounds before misoperation.

Open-circuit voltage curve comparison enables real-time battery SOH detection, reducing complex measurement needs and warning on degradation.

Code-transformed excitation and signal extraction enable battery impedance measurement during charging or discharging despite load interference.

Hybrid physics-informed ML uses cycling data and electrodynamic parameters to predict battery RUL, SOH, and SOC more reliably.

Electrode capacitance extracted during operation enables more accurate fuel cell stack degradation estimation for real-time health assessment.

Sampling times are tuned to each cell filter time constant to align phases and improve battery voltage and impedance measurement accuracy.

Existing power converters generate AC test signals to assess battery health in the field without added EIS chips or hardware upgrades.

Existing functional shift registers and flip-flops are reused as scan test points to raise coverage while limiting area, routing, and power overhead.

A shared battery measurement component keeps dual operating systems aligned, avoiding abrupt power level jumps when the foreground system changes.

A jumper-linked subsea loop cap enables continuity, bridge, and impedance tests that isolated dummy caps cannot support.

Grouped UEs exchange location estimates and uncertainty metadata to improve positioning accuracy while reducing GNSS sensing and power use.

Frequency-band impedance graphs and adaptive equivalent circuit selection improve lithium-ion battery state diagnosis accuracy and safety.

Charge pump voltage monitoring helps detect packaging microcracks in memory chips before leakage current causes high-voltage failures.

A one-piece conductive leaf spring probe with tubular ends cuts contact resistance, carries large currents, and simplifies socket replacement.

AC voltage sensing detects battery anomalies earlier than gas or pressure sensors, enabling faster pack disconnect without airtight enclosures.

Frequency-dependent impedance mapping estimates battery temperature, SoC, and SoH more precisely while avoiding full-spectrum measurement overhead.

Modified scan enable control keeps clock gating consistent during capture, improving LBIST defect detection accuracy and lowering power use.