Advances in power and digital control silicon technology over the past few decades have enabled a continuous improvement in motor-drive technology. When permanent-magnet, brushless-motor drives were first introduced to the market more than 20 years ago, the control algorithms were implemented using a combination of analog amplifiers and logic components. Today, highly integrated, mixed-signal controllers enable the implementation of complex control algorithms that maximize the efficiency of permanent-magnet AC motors.

Japanese air-conditioning manufacturers recently started switching from sensorless control based on back-EMF sensing, to sensor-less, field-oriented control based on current feedback. Field-oriented control (FOC) with current-angle phase-advance maximizes the efficiency of interior permanent-magnet motors, providing an efficiency gain of almost 5 percent. The switch from trapezoidal to sinusoidal control also minimizes torque ripple in order to reduce acoustic noise in the fan motor.

A recently introduced mixed-signal control IC can simultaneously run both the compressor and fan motors in an air conditioning system. A combination of highly optimized hardware control blocks and a configurable control sequencer enables rapid execution of complex motor control algorithms. The IC is one element in an appliance design platform that includes all the power and control silicon needed to drive the fan and compressor motor in an air-conditioning system. The same IC can also be applied to the latest energy-efficient laundry systems in Japan that use an energy-saving heat pump in the drying cycle.

Air-conditioner platform

Enlarge this picture Fig. 2. Sensorless field-oriented control algorithm.

The circuit schematic in Fig. 1 includes the major components in the outdoor unit controller for an air-conditioning system. The mixed-signal, motor-control IC drives the compressor motor, the fan motor, and the power factor correction circuit. The IC integrates three major functions: the Motion Control Engine (MCE), the Analog Signal Engine and an 8-bit microcontroller.

The MCE executes the motor control algorithms, while an independent 8-bit microcontroller core implements the application functions. The sensorless, field-oriented control algorithm derives all the required motor information from the currents flowing in the DC link shunts. This avoids the need for position sensors on the motor shaft and isolated current transducers in the power inverter circuit.

The Analog Signal Engine extracts the motor winding current from the DC link current signal by synchronizing the A/D converter sampling with the power-inverter device switching. The Motion Control Engine executes the sensorless FOC algorithm described by the control schematic in Fig. 2. The algorithm includes a reverse-rotation function that transforms the measured stator currents into a reference frame synchronized with the angle of the rotor-magnet flux.

The transformed currents have two quasi-DC components: a direct-axis current is aligned with the rotor flux, and a quadrature-axis component that generates motor torque due to interaction with the rotor magnet. The d and q axis current-loop compensators calculate the stator voltages to force the currents to track the set point values. The forward-rotation function transforms these voltages to sinusoidal AC voltages in the stator reference frame.

The space-vector PWM generator uses  these signals to derive transistor-switching signals for the 3-phase inverter. When driving a classical, permanent-magnet synchronous motor with surface-mounted rotor magnets, the d axis reference current is set to zero to maximize the torque per amp. However, when driving an interior, permanent-magnet motor, the d axis current will generate a reluctance-torque component to augment the torque produced by the rotor magnets. The IPM control function is the key control element that enables the operation at a higher efficiency when driving the IPM motor.

The other key feature of the sensorless FOC algorithm is that it does not require high-resolution rotor-angle sensors typically found in industrial-drive systems. In appliance drives, where-low speed performance is not important, the rotor angle can be derived from the winding back-EMF signal. In brushless DC drives with a 6-step commutation sequence, the back EMF is available directly by sampling the voltage on the unconnected winding.

However, when driving the motor with sinusoidal currents, the back EMF has to be calculated indirectly from the motor circuit model. The equations below describe the 2-phase equivalent circuit for the permanent-magnet, synchronous motor. The 2-phase currents are derived using the Clarke transform that calculates the currents in two quadrature windings that will produce the same field as the currents in the 3-phase windings. The 2-phase winding currents are the outputs of the forward rotation function that drive the space-vector PWM generator.

The important aspect of the 2-phase circuit model is that the back EMF terms are time derivatives of cosine and sine flux functions, and so they can be determined through integration. The detailed control schematic for angle and speed estimator shown in Fig. 3 has two major subsystems.

During the first stage, the flux estimator derives the rotor cosine and sine flux functions. The flux integrators include low-frequency gain compensation to avoid DC saturation. At the second stage, the rotor-angle, phase-locked-loop (PLL) forces the error between the rotor angle and the estimated angle to zero. The error is calculated using a vector-rotation function whose quadrature output will be zero when the rotation angle input matches the angle of the cosine and sine flux functions.

The second-order feedback loop in the PLL generates both angle and velocity signals. A further feature of the PLL is the start-up sequencer that is required at low speeds when the winding back-EMF signal is swamped by circuit noise. The first part of the start-up sequence is a parking function that drives DC current into the stator windings to align the rotor at a known angle. Then the motor is driven with a constant current to generate a constant torque. The PLL speed integrator is fed by a motor mechanical model that estimates the motor speed from the accelerating torque and system inertia. Once the motor reaches a certain minimum speed, the PLL switches to a closed-loop mode and tracks the rotor flux angle.

The motion control engine

Enlarge this picture Fig. 3. Rotor angle and speed estimator.

When using a traditional DSP or RISC processor, the motor-control schematic is first translated into state equations that are written in C code before software development tools can generate machine code for the processor. The Motion Control Engine supports a unique approach to motor-control algorithm development. The MCE graphical compiler is an algorithm development tool that transforms the control schematic directly to MCE sequencer code avoiding all intermediary steps.

This allows the developer to modify the control algorithm directly making use of a library of optimized control blocks such as PI compensators and vector rotations. One example of an optimized control block is the vector rotator shown in Fig. 4. The CORDIC vector rotation has been developed specifically for ASIC implementation that relies on a series of add, subtract, and shift functions that yield 12-bit accuracy in only 13 cycles [citation 1]. This calculation is 10 times faster than the calculation using Taylor expansion on a 32-bit RISC processor.

Enlarge this picture Fig. 4. Vector rotation hardware.

The optimized control blocks enable a significant reduction in execution time relative to software implementations. This allows the MCE to execute the sensorless field-oriented control algorithm twice in a PWM cycle and simultaneously control two permanent-magnet synchronous motors. This Analog Signal Engine includes a fast A/D converter, multiple sample and hold circuits and buffer amplifiers for signal conditioning that allow it to measure the winding currents in two motors. There is additional signal conditioning and MCE processing capacity to support the execution of a power factor control (PFC) algorithm. As a result, the air-conditioning control IC can control the input power factor, the fan motor, and compressor motor while traditional RISC-processor-based systems require separate fan and PFC control ICs.