Electrical Testing TRIZ Cases

Vertical fixation prevents rattling without increasing battery module dimensions or weight, avoiding conventional structural expansion.

A battery measurement device wirelessly transmits voltage data via magnetic field coupling to eliminate bulky high-voltage isolation components.

Clustering method fuses model parameters from similar batteries to improve state of health determination accuracy.

Integrated computational framework extracts battery charge profiles to estimate degradation.

Information processing apparatus generates sensor data combinations to evaluate recognizer performance.

A storing member with recessed portions reduces contact area to minimize static electricity adhesion of electronic components.

A modified Kalman filter estimates internal battery states to overcome slow diffusion and variability.

Sampling computational models to identify invalid operational regions and generate synthetic data for improved predictive accuracy.

A digital twin battery model predicts state of health using charge cycle data to resolve measurement precision issues caused by imprecise sensors.

A test strip circuit uses an operational amplifier to provide a pre-determined fraction of a reference voltage for analyte measurement.

Segmenting electrochemical cells into nanocells enables precise impedance prediction while reducing computational power consumption.

A large capacity battery system manages state of charge through dynamic bidding adjustments.

DRT-DOP model separates electrochemical processes using time-domain and frequency-domain signals.

High precision coulometry measures battery capacity losses through defined load patterns.

Differential pulse voltammetry estimates battery state by iteratively optimizing physics-based model parameters against measured current.

Dual sense circuits compare voltage thresholds against coil states to resolve detection reliability issues without increasing circuit complexity.

A battery model construction method reconstructs predictive models to enhance accuracy.

A cloud-based energy budget manager system tracks vehicle battery state of charge to verify sufficient power before executing function requests.

A battery management apparatus calculates disparate voltage values between secondary cells to identify degraded units during charging cycles.

A voltage drop detection system uses a parallel volatile memory and step-down circuit to monitor backup battery health.

A battery energy state estimation method uses pre-calculated lookup tables to determine remaining power from quadruplets of operational values.

A testing socket connects to a PCB ground layer through a cover-mounted conductive assembly.

Evaluation device generates representative voltage data from charge measurements to assess battery degradation without requiring new training databases.

A flexible eddy current probe uses a shape memory alloy to conform to test surfaces.

A battery state of charge estimation apparatus combines open circuit voltage and current integration methods using a Kalman filter to calculate error correction values.

A battery management system compares encoded channel indexes across separate tables to detect data misalignment between voltage values and overvoltage flags.

Programmable trim values in a temperature security module adjust thresholds for specific deployment modes, eliminating false positives from process variations.

A battery charging module determines state of charge to adjust cut-off voltage.

A battery sensor selects measurement pairs to determine internal resistance.

A processor manages power module charging cycles to maintain capacity.

Segmenting a cryptographic module into distinct operational modes allows developers to debug functions without compromising FIPS security standards.

A battery cell aging estimation method uses an equivalent circuit model to calculate maximum capacitance and state of charge from voltage and current data.

A battery tester uses a microprocessor to adjust variable load resistance for accurate cold cranking amperes detection.

Vertical segmentation of rigid and conductive materials in a multistage probe device resolves contact separation issues under mechanical load.

An integrated deep neural network predicts power electronic circuit health states using convolutional autoencoders and LSTM-RNN models.

A probe card holder uses L-shaped members and biasing mechanisms to securely hold the card.

A portable diagnostic device measures high voltage battery impedance using internal power processing.

Automated instruction generation transitions hardware resources to target states during pre-silicon design verification.

A battery diagnostic method uses adaptive current excitation signals to determine cell state variables accurately.

Parylene coating on anodized film perforated holes reduces particle generation from inner walls, improving inspection device durability.

Wireless temperature sensors on conductors calculate RMS currents through Joule heating, providing rapid outage detection and voltage regulation.

Segmenting processor logic allows Y logic to distribute clocks during X logic scanning, resolving simultaneous initialization bottlenecks.

A neural network maps electrochemical impedance spectroscopy signatures to quantify hydrogen crossover rates in operating PEM fuel cell stacks.

Intelligent electronic devices adjust alarm thresholds based on measured voltage events, reducing irrelevant alarms from static settings.

Smart multi-dimensional big data analyzing expert system monitors high-voltage circuit breakers through cloud database integration and dynamic warning modules.

A current measurement approach for electrical storage devices acquires quality data at predicted convergence timing.

Segmented monitoring tracks voltage, current, and temperature to predict remaining power levels and schedule replacements before failure.