Accurately predicting heat flux in coarse-grained CFD-DEM simulations is a significant challenge. Specifically, the rates of fluid-particle heat exchange, the effective thermal conductivity of a bed of particles, as well as radiative heat transfer rates are difficult to predict. By using a novel algorithm, we significantly improve the accuracy and stability of such simulations by using a heat exchange limiter. This limiter enables realistic predictions even at time steps that are three orders of magnitude larger than a typical fluid heat relaxation time. Additionally, view-factor-based corrections for radiative heat exchange computations are developed. These corrections ensure an effective thermal bed conductivity with less than 3 % error for a coarse-graining ratio of 10. The applicability of the P1 radiation model in coarse-grained settings is also examined, leading to recommendations for the CFD grid resolution to ensure accurate predictions. Our methods significantly enhance stability, accuracy, and computational efficiency, making coarse-grained CFD-DEM simulations more viable for industrial applications. These advancements enable more reliable modeling of high-temperature processes, accelerate optimization studies, and enable virtual equipment design of such processes.