Hybrid Power Source Control for Real-Time Engine Torque Fluctuation Offset
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Solution Overview
Problem
Existing technologies for hybrid vehicles lack an efficient method to predict engine torque fluctuations, which is crucial for effective reverse phase control of engine torque, and this prediction is not implemented in upper-level controllers like the hybrid control unit.
Innovation Solution
An apparatus and method for predicting engine torque fluctuations in hybrid vehicles using an upper-level controller, which includes a power source controller that predicts inertial and pressure torques based on engine RPM and required engine torque, and outputs a reverse torque instruction to offset these fluctuations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If engine control variables (valve timing, intake pressure, spark timing, air-fuel ratio, fuel quantity) are used to predict engine torque fluctuations, then prediction accuracy is improved, but device complexity and computation requirements increase significantly
Solution Approach 1:
The patent extracts only the essential parameters (engine RPM and required engine torque) needed for torque fluctuation prediction, separating them from the complete set of engine control variables. This extraction allows the upper-level controller to perform predictions without requiring all detailed engine control parameters, thus reducing complexity while maintaining prediction capability.
Solution Approach 2:
The prediction process is segmented into two distinct stages: an offline training phase where a neural network model is trained using comprehensive engine data, and an online execution phase where only simple parameters (RPM and required torque) are needed for real-time predictions. This segmentation allows complex computations to be performed beforehand, simplifying the real-time controller requirements.
2Measurement precision
If comprehensive engine control variables are used for real-time torque fluctuation prediction, then prediction accuracy is improved, but computation time and processing power requirements increase
Solution Approach 1:
The neural network model is trained offline in advance using comprehensive engine data and torque fluctuation patterns. This preliminary action prepares the model so that during real-time operation, only simple parameter lookups and calculations are needed, eliminating the need for complex real-time computations while maintaining high prediction accuracy.
Solution Approach 2:
The patent replaces complex real-time mechanical/computational analysis of multiple engine variables with a pre-trained neural network model that performs predictions based on simple input parameters. This substitution transforms the computation from a complex real-time process to a streamlined query-based system.
3Adaptability or versatility
If torque fluctuation prediction is implemented in the upper-level controller, then reverse phase control capability is improved, but the controller's computational burden increases
Solution Approach 1:
The patent extracts and uses only the minimal necessary parameters (engine RPM and required engine torque) for torque fluctuation prediction in the upper-level controller. By taking out only these essential parameters rather than requiring all engine control variables, the controller gains reverse phase control capability without bearing the full computational burden of comprehensive engine analysis.
Data Source
AI summary
An apparatus for controlling a power source of a hybrid vehicle, an operating method thereof, and a system including the same predict engine torque fluctuations in real time based on an engine RPM and a required engine torque. The apparatus includes a storage configured to store one or more algorithms for predicting engine torque fluctuations and one or more look-up tables (LUT). The apparatus has a power source controller configured to predict an inertial torque and a pressure torque related to an engine based on engine-related information and predict engine torque fluctuations based on the engine-related information, the inertial torque, and the pressure torque. The power source controller is further configured to output a reverse torque instruction to offset the engine torque fluctuations.


