Adaptive Power Optimization in Controller-Based Electronics
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Solution Overview
Problem
Controller-based devices, such as AC-DC power converters, face inefficiencies due to high power consumption from intensive calculations, which can lead to significant energy losses and reduced overall efficiency.
Innovation Solution
A method and apparatus that monitor and optimize power consumption by evaluating the cost of calculations against potential power savings, determining when and how frequently to perform calculations, and selecting algorithm complexity based on estimated power consumption and savings, allowing the device to decide whether to execute algorithms based on these comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If intensive calculations are performed to optimize operating parameters in real time, then the device operation is optimized, but the power consumption increases significantly
Solution Approach 1:
The system dynamically adjusts the calculation frequency and algorithm complexity based on operating conditions. The controller monitors parameters such as temperature, load, and efficiency metrics, and adaptively determines whether to perform intensive real-time calculations or use pre-calculated lookup tables, thereby optimizing the balance between operational performance and power consumption.
Solution Approach 2:
The patent changes the computational parameters by switching between different calculation modes (real-time calculation vs. lookup table usage) and adjusting algorithm complexity levels. This allows the system to reduce computational intensity when full optimization is not critical, thereby reducing power consumption while maintaining acceptable performance.
2Reliability
If real-time calculations are performed continuously, then the operating parameters are continuously optimized, but the computational overhead and power loss increase
Solution Approach 1:
Instead of continuous real-time calculations, the system performs calculations periodically or event-driven based on changes in operating conditions. The controller triggers calculations only when specific thresholds are exceeded or when operating conditions change significantly, reducing unnecessary computational overhead and associated energy losses.
Solution Approach 2:
The system pre-calculates and stores optimal operating parameters in lookup tables during system initialization or offline phases. During operation, the controller queries these pre-computed tables rather than performing intensive real-time calculations, significantly reducing computational overhead and power consumption while maintaining optimization benefits.
3Measurement precision
If complex algorithms are used to generate updated operating parameters, then the optimization accuracy improves, but the power consumption and execution time increase
Solution Approach 1:
The system applies partial action by using simplified algorithms or reduced-precision calculations when full optimization accuracy is not required. The controller assesses whether complex algorithms are necessary based on operating conditions, and if not, uses lighter computational approaches that consume less power while providing sufficient optimization accuracy.
Data Source
AI summary
A device and method are disclosed for optimizing self-power consumption. The device may sense one or more operating conditions of the device. The device may further select one or more operating parameters associated with at least one of the one or more operating conditions. The device may also estimate a power consumption associated with executing an algorithm to generate at least one updated value for at least one of the one or more operating parameters as well as estimate a power savings associated with operating using the updated value. The device may compare the estimated power consumption to the estimated power savings and determine whether to execute the algorithm based on the comparing.