Abstract
The present study elaborates the suitability of the artificial neural network (ANN) and adaptive neuro-fuzzy interface system (ANFIS) to predict the thermal performances of the thermoelectric generator system for waste heat recovery. Six ANN models and seven ANFIS models are formulated by considering hot gas temperatures and voltage load conditions as the inputs to predict current, power, and thermal efficiency of the thermoelectric generator system for waste heat recovery. The ANN model with the back-propagation algorithm, the Levenberg–Marquardt variant, Tan-Sigmoidal transfer function and 25 number of hidden neurons is found to be an optimum model to accurately predict current, power and thermal efficiency. For current, power and thermal efficiency, the ANFIS model with pi-5 or gauss-5-membership function is recommended as the optimum model when the prediction accuracy is important while the ANFIS model with gbell-3-membership function is suggested as the optimum model when the prediction cost plays a crucial role along with the prediction accuracy. The proposed optimal ANN and ANFIS models present higher prediction accuracy than the coupled numerical approach.
Highlights
In the last two decades, the researches on waste heat recovery technologies have been increased to diminish the global energy crisis [1]
Two experimental data sets for the development of a numerical method, artificial neural network (ANN) models and Adaptive Neuro-Fuzzy Interface System Modelling (ANFIS) models are considered as the training data set and testing data set of the thermoelectric generator system for waste heat recovery
The optimum ANN and ANFIS models are proposed from the comparison with experimental data using three statistical parameters of the coefficient of determination (R2 ), root mean square error (RMSE) and coefficient of variance (COV)
Summary
In the last two decades, the researches on waste heat recovery technologies have been increased to diminish the global energy crisis [1]. The thermoelectric generators are the evolving technology for the waste heat recovery due to its non-polluting and silent operational characteristics [2]. The significant research works have been done on the applications of the thermoelectric generators in the automobile vehicle for waste heat recovery. The low conversion efficiency of the thermoelectric generators restricts their commercialization in the automobile field [3]. To improve the performance of the thermoelectric generators in the waste heat recovery of the automobile vehicles, the hot heat exchanger is provided with various internal structures in the form of fins, inserts and protrusions
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