Electrical Testing TRIZ Cases

A climb-restricting ring on the probe main segment blocks solder rise at controlled height, improving cantilever probe card soldering stability.

Measured and model voltage feedback updates battery aging parameters to keep state estimation accurate under fast charging and harsh temperatures.

Multiple shunt sections and independent channels cross-check high-current readings, improving accuracy, redundancy, and temperature stability.

OCV-SOC point tracking estimates battery SOH from capacity variation and actual capacity, improving SOC and driving range accuracy.

Current and temperature measurements are combined with cut-off voltage and background current to estimate primary cell service life in real time.

Rotor-angle complex current summation detects current sensor gain errors under dynamic drive conditions, improving electric drive control accuracy.

Differentiating filters and feedback correction improve noisy battery cell internal resistance estimation for aging tracking and charge-discharge analysis.

Reconstruction-error analysis of normal battery behavior flags anomalies, assesses criticality, and signals likely error types.

Classifying complex battery usage patterns into representative groups speeds remaining-life prediction and keeps accuracy as batteries degrade.

Pre-setting combinational logic injects known scan values to pinpoint malfunctioning flip-flops and prevent corrupted DFT results.

Automated scoring, timing, and signal-based cable checks create a hands-on troubleshooting training environment with clear repair feedback.

Tracks battery health during charging and discharging by deriving an impedance indicator from current, voltage, and open-circuit voltage.

Nonlinear Kalman filtering combines battery data with reference and acceleration inputs to estimate SOH more accurately under complex deterioration.

Current change rate normalized by nominal capacity improves internal resistance consistency evaluation across reconfigurable battery modules.

Grouped scan gating masks X states at selected shift cycles, preserving compaction ratio and test coverage with lower on-chip test logic overhead.

Dynamic frequency switching by test pattern cuts fault detection time while balancing processor power use in intelligent driving IC checks.

An on-battery RC circuit lets a handheld NFC/RFID reader estimate remaining battery capacity from capacitor charge time without physical connection.

A multiplexer feeds scan insertion signals back to non-scan registers, improving IC test coverage without the area and power cost of full scan.

Sub-band voltage and current analysis enables online battery circuit estimation, cutting offline characterization time and improving parameter accuracy.

Tracking both position and type changes in differential-capacity feature points improves battery degradation diagnosis and identifies loss mechanisms.

An integral multi-beam cantilever pin replaces rigid pin and elastomer assemblies to cut debris, improve stability, and handle extreme temperatures.

A unified ESS battery analysis workflow automates log collection, pre-processing, and abnormality detection across multiple sites.

Unequal pad spacing creates a cross layout that fits more wafer scribe line TEGs while preserving probe card compatibility and process monitoring.

Hybrid long-term prediction and closed-loop power budgeting limits subsystem peaks before battery stress causes unexpected shutdown.

Dual gate control stabilizes timing exception path data during scan capture, cutting unknown values, test patterns, and test time.

A database-mapped workflow converts battery cycler binary test files into text automatically, avoiding per-cycler software installs.

ML surrogate models replace costly battery physics simulations to explore wider microstructure design spaces with faster, lower-cost optimization.

Real-time SOH and vehicle distance data are combined to map cumulative EV battery fire risk across multi-vehicle target areas.

Adaptive bit-depth sensing cuts synapse conductance errors while lowering ADC power use and improving neuromorphic response.

Cell-level test data and field-data retraining improve real-time EV battery SOHC estimation when BMS capacity values are inaccurate.

Detects abnormal battery cells by tracking voltage-drop inflection points during negligence tests to flag internal short-circuit risk.

Measured and estimated cell voltages are compared with Kalman filtering to detect abnormal voltage drops more reliably under noise.

Equivalent circuit parameters such as R0, R1, C1, and R1C1 improve battery SOH estimation by reducing noise and stabilizing accuracy.

Dual-stage X-masking filters unknown scan-test states by pattern and clock cycle, improving compaction quality and diagnostic resolution.

GAN-based test pattern generation automates DRC-compliant layout creation, improving validation accuracy and reducing manual review time.