Intelligent tires are one key element for autonomous self-driving cars and the Internet of Vehicles (IoV), especially if the battery-driven sensor systems attain the transition to be self-powered. Harvesting vibrational energy of these tire pressure monitoring systems (TPMSs) is the promising technique to make tire sensors self-sufficient and to provide additional energy for sophisticated algorithms, which constitute the intelligence of vehicle tires. Despite of two decades of intense research, no commercial product has been established. This work analyzes the technological reasons and presents both challenges and opportunities of TPMS energy transducers. First, this article specifies significant system requirements and characterizes common energy sources. The authors determine the necessary amount of energy on two different paths. A throughout comparison between different TPMS transducers overviews the state of the art, comprehensively. Typical TPMS energy harvesters are summarized, distinctive TPMS transducers are shortly presented and common problems are outlined, focusing on the harvesting mechanism, restoring force, interface circuit, and energy generation. The pros and cons of different energy transducer principles for their operation inside the tire are balanced. Focusing on reliability and on normalized energy generation, this publication highlights potent energy harvesters for system enhancement and gives recommendations for future developments. Two significant outcomes among others are to switch the focus from linear systems to systems with a nonlinear restoring force as well as to more efficient interface circuits than low-efficient full-wave rectifiers.

We present an approach to the schematic design and time-dependent simulation of microfluidic systems that are composed of basic components, such as pumps, channels, mixing junctions, and valves. For the schematic capture and the simulation, the Cadence Virtuoso design framework is employed, with the components modeled by Verilog-AMS. The pressures and flow rates are calculated with the help of the hydraulic analogy between electronics and fluidics. Signal flow quantities are used to express the flow of chemical concentration. Our focus is on systems employing chemofluidic transistors, i.e., hydrogel-based microvalves that facilitate autonomous flow control without the need for an external control unit. Our approach also covers layout editing by the use of programmed cells. The utility of the approach is exemplified by the successful top-down design of a chemofluidic oscillator circuit and by the functionally correct simulation of a chemofluidic SR flip-flop.

The unbelievable properties of our information processing capabilities regarding the processing of big data, resilience, and energy efficiency are inspiration sources for the optimization and the rethinking of the principles of electronic information processing. Here, we present an approach of integrated circuits intended to solve chemical problems by active processing of chemical information.