Wireless Battery Charger Adaptive Control Bandwidth
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Solution Overview
Problem
Current wireless vehicle charging systems face limitations in control bandwidth due to variable delays in wireless communication, leading to instability and inadequate response to system disturbances, which affects the reliability of the charging process.
Innovation Solution
An adaptive model is integrated into the feedback loop of the wireless electrical charging system, allowing for faster adjustment of output voltage based on real-time current and voltage data, using a system controller that calculates a voltage command value at a higher rate than data transmission, and varying parameters K0 and K1 to optimize power transfer across different power ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wireless communication channel is used for feedback loop, then wireless connection between power source and capture coil is maintained, but variable delays occur leading to control bandwidth restriction and system instability
Solution Approach 1:
The system performs preliminary actions by predicting future values of control parameters based on historical data and system models before actual disturbances occur. This allows the controller to proactively adjust system parameters, compensating for the delays inherent in wireless communication and effectively expanding the stable control bandwidth range.
Solution Approach 2:
The system implements a dual feedback mechanism: traditional feedback based on wireless communication for maintaining connection reliability, and predictive feedback using system models and historical data to compensate for communication delays. This combined approach resolves the contradiction by allowing reliable wireless connection while achieving precise control through model-based prediction.
2Stability of the object's composition
If traditional feedback loop is used with wireless communication, then system stability is maintained within limited bandwidth, but response to disturbances is too slow
Solution Approach 1:
The controller performs preliminary calculations to predict system behavior and determine optimal control actions before disturbances fully manifest. By using system models and historical data to forecast future states, the controller can prepare and execute corrective actions faster, improving response speed while maintaining stability through model-based predictions.
Solution Approach 2:
The system dynamically adapts its control strategy by switching between traditional feedback control and model predictive control based on operating conditions. This dynamic approach allows the system to achieve fast response when needed while maintaining stability through the robustness of traditional feedback, effectively resolving the speed-stability trade-off.
3Speed
If control bandwidth is increased for faster response, then response speed improves, but system becomes unstable due to wireless communication delays
Solution Approach 1:
The system introduces an intermediary predictive model that acts as a buffer between the wireless communication channel and the control actuator. This model predicts future system states and generates preliminary control commands, allowing the actual controller to operate at higher bandwidth without directly amplifying the destabilizing effects of wireless communication delays.
Solution Approach 2:
The system dynamically changes control parameters based on operating conditions and predicted system behavior. By adjusting controller gains and prediction horizons according to real-time conditions, the system can achieve fast response when stable while automatically reducing aggressiveness when instability risks arise, effectively managing the speed-stability trade-off through parameter adaptation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the control bandwidth, enabling quicker responses to system changes and improving the reliability of the wireless charging process by accurately predicting and adjusting power delivery, thus stabilizing the charging system.
Implementation Method 1
a source coil in electrical communication with the electrical power supply/inverter and configured to generate an alternating magnetic field
Implementation Method 2
a capture coil configured to be magnetically coupled to the source coil, thereby inducing the capture coil to capture the electrical power
Data Source
AI summary
A wireless electrical charging system and a method of operating same wherein operating parameters from a remote portion of the system are wirelessly transmitted to a system controller controlling the output voltage of an alternating power supply. The system controller executes an adaptive model control algorithm that allows the system controller to update the output voltage at a greater rate than the transmission rate of the operating parameters from the remote portion of the system.