Comprehensive evaluation of microwave reheating performance using predictive complementary relative phase shifting strategy in a solid-state system

Abstract

Solid-state microwave technology offers a potential solution to the nonuniform heating limitations of magnetron-based microwave ovens. A previously developed dynamic predictive complementary relative phase shifting strategy has demonstrated superior performance in simple model foods compared to fixed phase shifting approaches but needs evaluation on commercial/prepared meals and comparison with magnetron-based heating. This study comprehensively evaluated the reheating performance of solid-state microwave heating using the dynamic strategy across five commercial and/or prepared food products: Pulled Chicken (single component), Beef in Gravy (multicomponent), Lasagna (multilayer), Pulled Chicken & Lasagna (multicompartment), and Mashed Potato & Beef in Gravy (multicompartment), and compared their heating performances with that in domestic microwave heating with rotational turntable. Results revealed that the dynamic predictive complementary relative phase strategy significantly improved microwave heating performance across most food products compared to the magnetron-based heating. The predictive complementary algorithm dynamically selected relative phases that generated complementary heating patterns to the real-time heating performance. This led to an overall improvement of 4.6 % in the heating uniformity and 22.9 % on average temperature rise compared to the magnetron-based heating. Hence, this study confirms that predictive complementary relative phase shifting strategies present a promising advancement for next-generation solid-state microwave ovens, enabling more precise and efficient reheating of complex food matrices.