Code generation for embedded predictive control of gas water heaters

Abstract

Conventional control strategies usually employed in tankless gas water heaters present difficulty in controlling the hot water temperature when subjected to sudden changes in water flow rate. Inadequate control leads to temperature overshoots and undershoots with long settling times that severely affect the user comfort, increasing water and energy wastage and associated gas emissions. A strategy based on model predictive control is presented to reduce the impact of changes in hot water demand. A semi-empirical model, parameterized with experimental data and compatible with real-time simulation, is used for the heat cell. A tailored state observer is proposed, considering time-varying delays characterizing this thermal process. An automatic code generation software tool was developed for the embedded implementation of gas water heater predictive controllers. Numerical simulations and hardware-in-the-loop experiments were established to evaluate conventional and predictive control strategies. It was demonstrated that embedded model predictive control could be successfully implemented on computationally limited microcontrollers, even for thermal systems with extensive varying time delays. Predictive control has shown significant performance improvements, with decreased temperature fluctuations, a gain in comfort index from 36% to 75% and a reduction of up to 32 s in the settling time.