An observer based temperature estimation in cooking heterogeneous mixtures: a Turkish coffee machine application

A high-precision temperature information is required to follow the recipe in automatic cooking processes of heterogeneous liquids. Therefore, measurement equipment plays a crucial role in appliances developed for automatic cooking processes. However, it is difficult to obtain the temperature information in such appliances since the sensors cannot be located inside the heterogeneous liquid and the diffusion model is not precise in general. In this manner, a method is proposed to estimate the temperature of the heterogeneous mixture during the cooking process. This is achieved by the utilization of only one temperature sensor located at the outside wall of the cooking chamber in a commercial Turkish coffee machine. The temperature of this point with the sensor is considered as the output while the mixture temperature is assumed as an internal state, then a model is generated based on collected data in a special experimental setup. Experimental results show that the Turkish coffee can be cooked with required taste and consistency by the application of the proposed method.

PDF

___

[1] Lucía O, Maussion P, Dede EJ, Burdío JM. Induction heating technology and its applications: past developments, current technology, and future challenges. IEEE Transactions on Industrial Electronics 2014; 61 (5): 2509–2520. doi: 10.1109/TIE.2013.2281162
[2] Kilic VT, Unal E, Demir HV. Wireless metal detection and surface coverage sensing for all-surface induction heating. Sensors 2016; 16 (3) 363: 1–10. doi: 10.3390/s16030363
[3] Nagarajan B, Sathi RR, Vishnuram P. Fuzzy logic based voltage control scheme for improvement in dynamic response of the class D inverter based high frequency induction heating system. Turkish Journal of Electrical Engineering & Computer Sciences 2016; 24 (4): 2556–2574. doi: 10.3906/elk-1403-57
[4] Lasobras J, Alonso R, Carretero C, Carretero E, Imaz E. Infrared sensor-based temperature control for domestic induction cooktops. Sensors 2014; 14 (3): 5278–5295. doi: 10.3390/s140305278
[5] Paesa D, Franco C, Llorente S, Lopez-Nicolas G, Sagues C. Adaptive simmering control for domestic induction cookers. IEEE Transactions on Industry Applications 2011; 47 (5): 2257–2267 . doi: 10.1109/TIA.2011.2161629
[6] Paesa D, Llorente S, Sagues C, Aldana O. Adaptive observers applied to pan temperature control of induction hobs. IEEE Transactions on Industry Applications 2009; 45 (3): 1116–1125. doi: 10.1109/TIA.2009.2020189
[7] D’Antona G, Santacatterina G, Seifnaraghi N, Brindani F. Water temperature estimation in induction cooker for higher energy efficiency. In: IEEE 2014 International Instrumentation and Measurement Technology Conference; Montevideo, Uruguay; 2014. pp. 525–529.
[8] Franco C, Acero J, Alonso R, Sagues C, Paesa D. Inductive sensor for temperature measurement in induction heating applications. IEEE Sensors Journal 2011; 12 (5): 996–1003. doi: 10.1109/JSEN.2011.2167226
[9] Derossi A, Ricci I, Caporizzi R, Fiore A, Severini C. How grinding level and brewing method (Espresso, American, Turkish) could affect the antioxidant activity and bioactive compounds in a coffee cup. Journal of the Science of Food and Agriculture 2018; 98 (8): 3198–3207. doi: 10.1002/jsfa.8826
[10] Cordoba N, Fernandez-Alduenda M, Moreno FL, Ruiz Y. Coffee extraction: A review of parameters and their influence on the physicochemical characteristics and flavour of coffee brews. Trends in Food Science & Technology 2020; 96: 45–60. doi: 10.1016/j.tifs.2019.12.004
[11] Fuller M, Rao NZ. The effect of time, roasting temperature, and grind size on caffeine and chlorogenic acid concentrations in cold brew coffee. Scientific reports 2017; 7 (1): 1–9. doi: 10.1038/s41598-017-18247-4
[12] Klotz JA, Winkler G, Lachenmeier DW. Influence of the Brewing Temperature on the Taste of Espresso. Foods 2020; 9 (36): 1–5. doi: 10.3390/foods9010036
[13] Ellero M, Navarini L. Mesoscopic modelling and simulation of espresso coffee extraction. Journal of Food Engineering 2019; 263: 181–194. doi: 10.1016/j.jfoodeng.2019.05.038
[14] Tan AÖ, Bursa N. Turkish coffee: arte and factum–paraphernalia of a ritual from ember to cup. In: McWilliams T (editor). Food & Material Culture: Proceedings of the Oxford Symposium on Food and Cookery. Prospect Books, 2014, pp. 314–324.
[15] Hu YC, Chen PJ, Chang PZ. Thermal-feature system identification for a machine tool spindle. Sensors 2019; 19 (5): 1–24. doi: 10.3390/s19051209
[16] Fraden, J. Handbook of modern sensors. Vol. 3. New York: Springer, 2010.
[17] Luenberger DG. Optimization by vector space methods. John Wiley & Sons, 1997.
[18] Hazir, S, Hasanreisoglu L, Kayalar G, Simsir B, Albas E. A coffee machine and a coffee preparation method. Arcelik Anonim Sirketi, Google Patents, 2006.