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Implantable medical biosensors are commonly used to treat health problems via the unobtrusive collection of medical data such as neural activity or cardiac pacemaker status. Because they are required to operate continuously, sufficient electrical power is essential. Rechargeable lithium-ion (Li-ion) batteries are a good power source for implants due to their small size, high energy density, low self-discharge rate, and long lifespan. Wireless battery charging allows the implantable medical devices to harvest RF energy. Typically, this can be accomplished through inductive coupling or far-field waves, but both have limitations.
National Cheng Kung University (NCKU) in Taiwan used Keysight Technologies’ Advanced Design System (ADS) software to investigate an approach to overcome such limitations. They created a DC-driving impedance matching method for wireless charging using the medical implant communication service (MICS) band. ADS simplified the development and implementation of both the matching network and the rectifier-antenna (rectenna) subsystem. The team performed electromagnetic (EM) and circuit co-simulation, and thus explored the design space.
Wirelessly charging Li-ion rechargeable batteries in implantable medical biosensors is tricky, as RF power must be transmitted through skin tissue from an external transmitting device. For NCKU, the wireless battery charger had to fit within a 14-mm-diameter disk, and include a printed circuit antenna that could operate over the MICS band, a matching network, two rectifier diodes, and an LC low-pass filter. The challenge was to recharge the Li-ion cell, with its 10-mAh capacity, in five hours (a so-called 0.2-C rate). Complicating matters was the battery’s resistance, reactance, and cell voltage, which varied dramatically with its state of charge, making it difficult to determine what load to optimize the matching network for the dynamics of the load. Furthermore, the traditional method of impedance matching uses a DC resistive load to decide the rectifier’s impedance, which introduces loss because of the mismatch between the rectenna and Li-ion battery.
To overcome these challenges, a new impedance matching method was required — one that adopted the output DC current of the dual-diode rectifiers to establish a simple equivalent model for wireless battery charging. To do that, researchers from NCKU turned to ADS, with its ability to perform EM and circuit co-simulation.
To create the impedance matching model, researchers used ADS harmonic balance to simulate the dual-diode rectifier circuit and explore the design space. A sweeping method — whereby the resistance values and custom Li-ion battery potentials are swept, and corresponding output voltage, current, and impedance recorded — was then used to match impedance between the Li-ion battery and rectenna. Next, the model was used to create an optimized rectenna circuit consisting of just three capacitors, one inductor, two diodes, and the PCB itself (with both the interconnect and MICS band implantable antenna). Finally, the implantable rectenna was designed using ADS EM circuit co-simulation. Using this feature, researchers ensured the rectenna experienced reduced EM loss on human tissue and in turn, improved radiation characteristics.
With this approach, NCKU researchers developed a simple, yet effective DC-driving impedance matching method for rectennas and wirelessly charging implantable Li-ion rechargeable batteries. For 10-dBm input RF power, researchers achieved a 76% RF-to-DC conversion efficiency of incident power to battery charging power averaged over a five-hour charge cycle. In contrast, comparable prior work achieved only a 50% conversion efficiency.
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