In the old days, it was common to excite the sin and cos windings with sinusoidal signals that were 90 degrees out of phase (sin and cos). Then when the shaft rotates, the rotor winding produces a fixed amplitude sine wave, whose phase shifts in proportion to the shaft angle. The control system must then resolve the phase angle of the rotor winding against a reference wave. This was a relatively easy thing to do with analog circuitry. The reference waveform could be the position command signal. The command signal to the actuator is then proportional to the phase error between the resolver rotor and the reference signal.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
Using Siemens NX software, a team of engineering students from the University of Michigan built an electric vehicle and raced in the 2013 Bridgestone World Solar Challenge. One of those students blogged for Design News throughout the race.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.