By Khagendra Thapa, VP of Business Development of Current Sensing business, Aceinna
The latest trends in personal electronics have placed a lot of pressure on embedded system developers. When it comes to consumer and medical wearables, advanced personal electronics and the IoT, the smaller, more functional and longer-lasting, the better. Similarly, industrial and automotive applications are pushing boundaries to achieve smaller, more efficient, reliable and robust systems. Significant improvement in all of these include lowering parts count, simplifying circuitry and increasing operational efficiency.
Many of these advances are related to user functionality, like Cloud-based Internet of Things (IoT) solutions that rely on next-generation RF technologies. Other rapidly-emerging current-sensing applications include electric vehicles (EVs) and their advanced driver-assistance systems (ADAS) and autonomous driving requirements.
Current-sensing technologies are important in small precision-control and protection electronic circuits needed for devices to be cost-effective and efficient. Precision needs feedback, and current sensing provides the critical performance information an embedded intelligent system needs to manage itself.
There are many EV development efforts right now, with focus on improving the efficiency of the powertrain, motors and on-/off-board charging systems, as well as the performance of the battery pack, since all these are directly related to the vehicle’s range and charging efficiency. Current sensing delivers significant advantages in these applications.
Since motors are using most of the power, any improvement there will cascade benefits throughout the system, from increasing the EV’s range to reducing its thermal problems. When it comes to driving motors, the switching frequencies and control mechanisms are critical.
Effective motor control requires accurate performance measurement, and current sensors play an effective role here. For the motors’ condition monitoring, fast current sensors help measure and monitor the motor’s ripple currents to determine lifetime and performance parameters. On the protection side, current sensors support safety by improving the control, accuracy and reliability of the motor drive.
Many EV power electronics and charging systems are migrating to advanced wide-bandgap semiconductors like Silicon Carbide (SiC) and Gallium Nitride (GaN), which offer higher switching frequencies and efficiencies. A significant benefit of faster switching is the ability to shrink the size of the passives and magnetics in a circuit, with direct size and weight benefits.
However, when a circuit is switching faster, the ability to measure the performance parameters must keep up, too. Monitoring the circuit in real time advances functionality like dynamic control of the power switching and motor drive frequency, as well as reliable and fast fault-detection.
In the related area of electric trains, industrial machines, traction and robotics, we are starting to see the use of reluctance motors, a winding-free design that generates torque through magnetic reluctance. Available in synchronous, variable, switched and variable-stepping configurations, reluctance motors can deliver high power density at low cost.
The problems with reluctance motors include high torque ripple at low speed and the resulting noise. In addition, because of the extremely high temperatures involved, reluctance motors are typically used with a separate harness and control system. Advanced solutions using wide-bandgap semiconductor sensors can take more heat, enabling size, weight and complexity reductions of the overall system.
Figure 2: Variable switched reluctance motors can deliver high power density
Constructed without copper coils in the rotor, reluctance motors can be lighter than their electric motors’ counterparts. However, the required control system is very complex, because if the current is not accurately controlled, which is related to torque, torque ripple will appear, generating noise. Advanced fast current-sensing improves control of the ripple current, which provides lower noise and a more reliable solution.
It’s important to bring up the protection side again because, in high-power systems, it might be worth switching the whole power stage off in 1.5us. If considering a shutdown-time budget, then the step response needs to be less than 500ns, which will become more stringent when migrating to higher power and frequency levels.
Power factor correction
Used to reduce the lagging power factor in inductive loads, power factor correction (PFC) compensates for the phase difference between voltages and current, since when the power factor drops, the system becomes less efficient.
To get 1kW of real power at a power factor of 0.2, 5kVA of apparent power needs to be transferred, i.e. 1kW ÷ 0.2 = 5kVA. This, obviously, can severely impact the performance in inductive loads such as motors, refrigerators and HVAC systems, inverters, uninterruptible power supplies (UPS) and similar systems.
Fast turn-on/-off time, fast reverse recovery and lower ON resistance of SiC- and GaN-based power switches are allowing effective use of totem-pole PFC topology for better efficiency and a lower number of components. For example, when it comes to ripple currents in the PFC in a totem-pole configuration, to measure current cycle-by-cycle to calculate the pulse-width modulation (PWM) duty ratio, the bandwidth needs to be high to successfully match the circuit’s switching frequency. If, say, the PFC switching frequency is 65, 140, 200 or 300kHz, ideally, for the current sensor, the bandwidth should be ten times the switching frequency.
In smart manufacturing and the smart factory, for example, it comes down mostly to automation and data exchange. In a system where powered devices are connected to an intelligent infrastructure and the Internet, there’s the need for power conversion. Power monitoring and management are critical to the optimal operation of smart assembly processes, with everything being measured in real time. With a highly-accurate sensor, these processes can be optimised, and efficiency and productivity improved.
This performance can be further improved by using AMR current sensing (see ‘AMR current sensing’box) to determine processor utilisation trends, especially for applications involving AI, the Cloud and data storage. AMR current sensors can also apply power tracking for performance monitoring, optimisation of processor loading and its thermal management.
Whether for advanced EVs or entire smart factories, UPSs, inverters or motor drives, efficient and cost-effective power management is key to these systems’ optimal performance. In applications from driving motors to powering 5G systems, operation is expected to be faster and more effective. Advanced current sensing enables higher levels of control, with greater efficiencies at higher frequencies.
AMR current sensing
Aceinna’s solution to current sensing is based on its Anisotropic Magneto-Resistive (AMR) technology. The AMR current sensor is isolated, and it doesn’t require additional components other than a decoupling capacitor.
Compared to other current-sensing methods (Figure 3), an AMR sensor is a compact and high-performance solution.
For example, when using a shunt resistor, this is inherently a non-isolated solution. A current transformer is bulkier than an AMR-based current sensor and it only works with AC, whereas the AMR current sensor responds to both DC and AC bi-directional current. And, compared to a Hall-effect sensor, AMR technology offers a 1.5MHz bandwidth, and has a lower offset and noise.
Figure 3: Advantages of AMR-based current sensing versus other types of current-sensing technologies
Figure 4: Aceinna current sensors use a U-bend with two AMR sensors to cancel out external fields
Within the Aceinna sensor, current flows through a U-bend in the lead frame (Figure 4), where it generates a forward or reverse field measured by two current sensors in the device. By measuring the field from both current directions, the device cancels out external fields and magnetic anomalies that might be present. This allows a horizontally-sensing AMR chip to ignore external fields generated from other nearby components on the board.