Parallel Power Converter MPC Using Full Switching State Selection
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Solution Overview
Problem
Existing single-vector-based finite control set model predictive control (FCS-MPC) methods for two parallel power converters cannot effectively optimize line currents and circulating currents simultaneously due to limited optimization options, as they only consider a subset of available control actions and ignore the complete set of 64 switching states.
Innovation Solution
A novel single vector-based FCS-MPC method that establishes comprehensive mathematical models for line and phase-circulating currents, constructs a mapping relationship between key indicators and switch combinations, and uses a novel cost function with dynamic weight coefficients to select optimal control actions from the complete set of 64 available control actions, reducing computation time and enhancing overall performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional PWM strategies are used for control, then the control implementation is simple, but multi-objective optimization cannot be achieved
Solution Approach 1:
The patent transforms the control approach by changing the fundamental parameters evaluated in each control cycle. Instead of fixed PWM switching, the system dynamically evaluates multiple switching state combinations and selects optimal states based on real-time cost function calculations that consider multiple objectives simultaneously (line current quality, phase-circulating current, zero-sequence circulating current).
Solution Approach 2:
The control system transitions from static PWM strategies to dynamic model predictive control where the optimal control actions are determined in real-time based on current system state. The cost function and switching state selection adapt dynamically to changing operating conditions, enabling multi-objective optimization while maintaining computational feasibility through structured evaluation methods.
2Manufacturing precision
If two-stage FCS-MPC is used to optimize line current, then line current quality improves, but circulating current control is compromised
Solution Approach 1:
The patent merges the previously separate two-stage control approaches into a unified single-stage FCS-MPC framework. Both line current optimization and circulating current suppression are integrated into a single cost function that evaluates all switching state combinations simultaneously, ensuring both objectives are considered together in the optimal control decision.
Solution Approach 2:
The control method achieves multi-functionality by designing a comprehensive cost function that simultaneously addresses multiple control objectives: line current quality improvement, phase-circulating current suppression, and zero-sequence circulating current minimization. A single control action selection process optimizes all these aspects together rather than requiring separate dedicated control stages.
3Adaptability or versatility
If the complete set of 64 switching states is evaluated, then optimization options increase, but computation time increases
Solution Approach 1:
The patent segments the evaluation of 64 switching state combinations into systematic groups based on voltage vector characteristics and circulating current suppression requirements. By organizing states into structured categories with predetermined evaluation priorities, the computational burden is reduced while maintaining comprehensive optimization capability across all switching states.
Solution Approach 2:
The control method performs preliminary classification and grouping of switching state combinations before detailed cost function evaluation. Switching states are pre-organized based on their voltage vector properties and potential impact on circulating currents, allowing the system to efficiently navigate through all 64 combinations by evaluating groups rather than individual states in isolation, thus reducing overall computation time.
Data Source
AI summary
This invention proposes a single-vector-based finite control set model predictive control for two parallel power converters, which adopts a centralized control structure to achieve accurate control of overall performance. It establishes predictive models for line currents and three phase-circulating currents and constructs a novel cost function that uses these currents as performance indices to implement the predictive control algorithm based on the proposed predictive models. The invention proposes dynamic weighting coefficients and adjustment principles to improve system control performance. A finite set output signal matrix containing important characteristic information of all alternative vectors is constructed to avoid redundant calculations in each control horizon, reducing computation time during practical implementation. This invention addresses the limitations of existing one-vector-based FCS-MPC for two paralleled power converters, which controls each sub-converter individually with a set of available eight control actions and cannot effectively regulate the overall performance of the two paralleled power converters.