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Structural and morphological interplay between hard and soft phases determine the bulk properties of thermoplastic polyurethanes. Commonly employed techniques rely on different physical or chemical phenomena for characterizing the organization of domains, but detailed structural information can be difficult to derive. Here, total scattering pair distribution function (PDF) analysis is used to determine atomic-scale insights into the connectivity and molecular ordering and compared to the domain size and morphological characteristics measured by AFM, TEM, SAXS, WAXS, and solid-state NMR 1 H– 1 H spin-diffusion. In particular, density distribution functions are highlighted as a means to bridging the gap from the domain morphology to intradomain structural ordering. High real-space resolution PDFs are shown to provide a sensitive fingerprint for indexing aromatic, aliphatic, and polymerization-induced bonding characteristics, as well as the hard phase structure, and indicate that hard phases coexist in both ordered and disordered states.

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Sensorless control approaches for low and zero speed determine the rotor position by injecting high frequency voltage signals. Current measurement noise and quantization necessitate a minimum amount of injection amplitude, which implies an acoustic noise emission that for many applications is unacceptable. This paper proposes to sample the current with the maximum A/D conversion frequency while processing the data with an FPGA. By means of a recursive least squares method and a algorithmic extension, high precision current slopes are calculated from low injection voltage. Experimental results show that the injection magnitude can be reduced by factor 7 to 10 compared to standard PWM centered current measurement.

No abstract