Transport System Parameter Adaptation via Power Model Feedback
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Solution Overview
Problem
Existing methods for determining system parameters in transport systems, such as elevator systems, suffer from inaccuracy, leading to errors in load measurement and control, which affects the efficiency and maintenance of the systems.
Innovation Solution
A method that uses a power model to adapt transport system parameters by determining a first and second input parameter, updating the power model, and adjusting status parameters based on these inputs, allowing for more accurate parameter adaptation with reduced measurement data, enabling efficient power flow modeling across different parts of the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calculation or testing methods are used to determine system parameters, then the process is simple, but the accuracy of parameter determination is poor
Solution Approach 1:
The invention implements a feedback mechanism where measured power consumption values are continuously compared with model-calculated values, and the model parameters are automatically adjusted to minimize the difference. This closed-loop feedback system enables high measurement precision through iterative optimization without requiring complex manual calibration procedures.
Solution Approach 2:
The invention replaces traditional mechanical testing and manual parameter determination methods with an electronic/power-based measurement system. By measuring electrical power consumption and using a mathematical power model, the system substitutes complex mechanical testing procedures with simpler electrical measurements and computational analysis.
2Measurement precision
If a large number of parameters are adapted, then the model accuracy improves, but the amount of measurement data required increases significantly
Solution Approach 1:
The power model is segmented into multiple independent components, each representing a specific physical element (motor, transmission, load, etc.) with its own parameters. This segmentation allows the system to adapt parameters in modular fashion, reducing the amount of data needed for each adaptation step while maintaining overall model accuracy through cumulative refinement.
Solution Approach 2:
The invention performs preliminary parameter adaptation using available measurement data before full-scale operation. By initially adapting parameters with limited data and then progressively refining them during normal operation, the system achieves high accuracy without requiring all measurement data to be collected upfront.
3Reliability
If power model parameters are adapted using measured data, then the model fits actual power consumption better, but the system complexity increases
Solution Approach 1:
The parameter adaptation system is self-service in nature, automatically adjusting model parameters using built-in measurement capabilities and computational algorithms. The system performs self-calibration without requiring external intervention or complex adjustment mechanisms, thereby improving reliability while maintaining manageable system complexity.
Solution Approach 2:
The invention focuses on adapting a specific set of critical power model parameters rather than all possible system parameters. By selectively changing only the most influential parameters (motor efficiency, transmission losses, load characteristics), the system achieves significant improvements in power model accuracy without proportionally increasing overall system complexity.
Data Source
AI summary
The invention relates to an arrangement and a method for the adaptation of parameters in a transport system. The arrangement of the invention comprises a power model (1), wherein power flow in the transport system is described by means of transport system parameters (2, 3, 4, 13), which include input parameters (2, 3, 13) and status parameters (4). The arrangement also comprises the determination of at least a first (2) and a second (2) input parameter, and the power model (1) is updated on the basis of at least the first input parameter (2). At least one transport system status parameter (4) is adapted using at least the updated power model (1) and the second input parameter (3) thus determined.