The accelerating electrification of transportation, rapid expansion of renewable energy infrastructure, and increasing demand for industrial automation are driving a critical need for highly efficient and reliable power electronics. This technology directly addresses these trends by optimizing power device performance, enabling longer EV ranges, more stable grid integration for renewables, and reduced operational costs for industrial machinery, positioning it as a key enabler for next-generation energy systems.
Reduces power loss by up to 15% compared to conventional methods by optimizing switching patterns based on specific requirements.
Reduces surge voltage by over 20% by calculating optimal gate terminal application patterns, thereby extending device lifespan and reducing stress.
Automates and accelerates optimal pattern discovery, significantly reducing the time and effort traditionally spent on manual adjustments or complex simulations.
This patent protects a computing device and method for easily identifying optimal switching patterns for power devices, specifically by taking required values for power loss or overshoot voltage and calculating the appropriate switching pattern. The claims are considered robust, having successfully overcome a rejection, indicating clear differentiation from prior art and a stable scope of protection.
This patent primarily covers the software logic for optimizing switching patterns. White space exists in developing novel power device materials, advanced thermal management solutions, or integrating this optimization with predictive maintenance AI for broader system-level improvements.
Assuming an annual electricity consumption of 50 GWh for a large-scale factory, an electricity unit price of $0.13/kWh (AI est.), and a 5% reduction in power loss due to this technology, an annual electricity cost saving of ~$325K (AI est.) could be realized. Furthermore, anticipating a 10% extension in device lifespan and a halving of device replacement frequency due to surge suppression, an additional ~$1.3M (AI est.) in annual maintenance cost savings is projected, totaling ~$1.6M (AI est.) in potential annual cost reductions.
X: Energy Efficiency Improvement
Y: System Stability & Longevity