Stable Point Recognition and Data Correction in Electric Drive Efficiency Testing

The efficiency of a powertrain under various operating conditions reflects its driving characteristics and fuel consumption performance, providing a basis for determining optimal speed ranges and acceleration/deceleration strategies. Traditional efficiency mapping requires exhaustive operating point testing and subsequent data processing (e.g., outlier removal, retesting), which suffers from long testing cycles and insufficient bench intelligence, compromising efficiency and accuracy. To address this, this study proposes a rapid efficiency testing and processing method that integrates testing and data analysis on the test bench. By incorporating intelligent algorithms for real-time data filtering and adaptive control, the approach significantly improves accuracy and reduces testing time.