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Grinding requires high specific energy which develops high temperatures at wheel work piece interface. High temperatures impair work piece quality by inducing tensile residual stress, burn, and micro cracks. Control of grinding temperature is achieved by providing effective cooling and lubrication. Conventional flood cooling is often ineffective due to enormous heat generation and improper heat dissipation. This paper deals with an investigation on using TRIM E709 emulsifier with Al2O3 nanoparticles to reduce the heat generated at grinding zone. An experimental setup has been developed for this and detailed comparison has been done with dry, TRIM E709 emulsifier and TRIM E709 emulsifier with Al2O3 nanoparticles in grinding EN-31 steel in terms of temperature distribution and surface finish. Results shows that surface roughness and heat penetration were decreased with addition of Al2O3 nanoparticles.

Open end winding induction motor (OEWIM) drives are better alternate for multi-level inverter fed induction motor drives. OEWIM drives can be used in industries and electric vehicles but they entail ripple-free torque. Predictive torque control (PTC) strategy offers high dynamic performance and lesser ripple in torque, flux when compared with direct torque control. Classical PTC involves high switching frequencies and empirical methods to select weighting factors. The selection and tuning of weighting factors are cumbersome. In this article, a new normalised weighted sum model (WSM) based PTC of four-level inverter fed OEWIM is introduced to curtail torque, flux ripples, switching frequency and enhance the selection of weighting factors. The proposed algorithm uses multi-objective cost function and the optimisation of cost function is performed by using normalised WSM. The normalisation of individual cost function simplifies the selection of weighting factors to select optimal voltage vector. As a result, the proposed PTC offers all the features of classical PTC and overcomes the difficulties involved in classical PTC. Simulation and experimental studies are performed on dual inverter fed OEWIM with four-level inversion. The effectiveness of proposed algorithm is verified by comparing proposed PTC algorithm with classical PTC algorithm.

This study proposes direct torque and flux control of dual-inverter-fed open-end winding induction motor (OEWIM) with the help of model predictive control. OEWIMs are extensively used in electric vehicles and for ship propulsion but they require a high dynamic performance. Predictive torque control (PTC) retains the features of direct torque control and offers a high dynamic performance by eliminating start-up problems. In this study, predictive torque control is implemented for multilevel inversion-fed OEWIMs. Multilevel inversion is obtained by operating two two-level inverters with equal and unequal DC link voltages. The proposed study gives a comparative analysis of PTC of OEWIM for various speeds and numerical analysis of torque ripple and flux ripple. The proposed methods are simulated using MATLAB/SIMULINK and experimental response shows the validity of the developed methods.

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