一种车辆空调系统仿真模型降阶方法及存储介质
By reducing the complexity of the vehicle air conditioning system simulation model through box-based operations and artificial neural network models, the problem of low computational efficiency of high-precision simulation models is solved, enabling efficient simulation analysis and control strategy optimization.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHONGQING UNIV
- Filing Date
- 2025-06-10
- Publication Date
- 2026-07-17
AI Technical Summary
Existing high-precision vehicle air conditioning system simulation models suffer from low computational efficiency, making them unsuitable for control strategy optimization and rapid analysis and evaluation of design schemes.
The initial training case set is constructed by binning, effective training cases are selected, an artificial neural network model is constructed, the complexity of the simulation model is reduced, and the model is trained using effective training and validation datasets.
While maintaining the necessary simulation accuracy, it improves computational efficiency, simplifies the simulation model, and is suitable for rapid analysis and control strategy optimization, avoiding transient disturbances and enhancing model fitting ability.
Smart Images
Figure CN121031257B_ABST