Glass Antenna Design Using EM Simulation and Optimization
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Solution Overview
Problem
Existing glass antenna designs face challenges in achieving optimal performance across various vehicle types, sizes, and shapes, particularly due to manufacturing costs, noise suppression issues, and the need for frequent redesigns with new vehicle models, which complicates mass production and affects broadcast signal reception.
Innovation Solution
A method combining an EM simulation tool with an optimization algorithm to automatically design glass antennas, optimizing performance by adjusting equivalence coding conditions, mesh numbers, and initial prototypes, and applying techniques like Pareto-Cost optimization and strip line simplification to ensure optimal performance and manufacturability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If glass antenna design is customized for each new vehicle model, then antenna performance is optimized, but design time and cost increase
Solution Approach 1:
The patent applies preliminary action by establishing a standardized antenna design and equivalence coding system that can be pre-configured for different vehicle types. This allows the antenna design to be quickly adapted to new vehicle models without starting from scratch, thus optimizing performance while reducing design time.
Solution Approach 2:
The patent creates a universal design framework that can accommodate multiple vehicle types and glass configurations through equivalence coding. The standardized antenna design can be applied across different vehicle models by adjusting parameters rather than creating entirely new designs, reducing both time and cost.
2Reliability
If complex optimization algorithms are used to optimize antenna performance, then antenna performance improves, but computational time and complexity increase
Solution Approach 1:
The patent segments the optimization process into distinct stages: equivalence coding establishment, initial design configuration, and performance optimization. This segmentation allows each stage to be handled with appropriate complexity levels, reducing overall computational burden while maintaining performance optimization.
Solution Approach 2:
The patent optimizes antenna performance by adjusting key parameters such as strip line dimensions, glass antenna geometry, and equivalence coding conditions rather than redesigning the entire system. This parameter-based optimization reduces computational complexity compared to full-system optimization.
3Object-affected harmful factors
If noise suppression is prioritized in glass antenna design, then signal quality improves, but design flexibility and manufacturing ease decrease
Solution Approach 1:
The patent uses equivalence coding to create simplified representations of the glass antenna system that capture the essential noise suppression characteristics without requiring complex physical structures. This allows noise suppression to be achieved through standardized coding patterns that are easy to manufacture.
Data Source
AI summary
The present invention features a technique comprising the design of a glass antenna having a desired performance regardless of the kind of vehicle and the glass size and the shape of vehicle, by operating an EM (engineering model) simulation tool with an optimization algorithm.