System-level Modeling Approach Research Articles

A behavioral nonlinear modeling implementation for MEMS capacitive microphones

We are highlighting the behavioral nonlinear system-level modeling approach for MEMS capacitive microphones. The combination of finite element modeling and large signal nonlinear circuit modeling provides a strong capability to predict electroacoustical performance for capacitive transductions. Circuit simulation tools such as Cadence Virtuoso have emerged as powerful aids in designing behavioral models in both linear and nonlinear regimes. Typical small signal lumped element models fail to capture the MEMS behavior which changes over pressure and electrical bias conditions. The models described herein capture diaphragm displacement and capacitance change over large pressure ranges for a simply supported circular plate. This can be coupled with the electrostatic force, due to the applied bias voltage, and converted back to pressure, thereby realizing a feedback loop in the circuit model. The nonlinear model capability is extended to predict capacitance-bias behavior and estimate pull-in of the MEMS device. The microphone sensitivity, signal-to-noise ratio, and harmonic distortions are accurately predicted using the nonlinear large signal model when compared to measured microphone data.

Multi-domain system level modeling approach for assessment of degradation behaviour under thermal and thermo-mechanical stress

Within the scope of this work, a multi-domain system modeling approach that is compatible with various electronical components and subsystems used in automotive and railway applications is to be developed. This approach serves the development of a hybrid, model-based condition monitoring of complex electronic and mechatronic systems. It aims at the implementation of condition monitoring in relevant applications of automotive and railway technology, e.g., safety-relevant electronic systems for train control and control units of electrified automobiles. Furthermore, the multi-physics modeling of the mentioned electronic components is performed using different object-oriented simulation environments, such as Simulink and OpenModelica11Simulink® and Modelica® are registered trademarks. in order to obtain as much information as possible that is relevant for the reliability assessment of the modeled systems. The approach is applied on two common example circuits used in complex electronic systems, a clocking circuit with a crystal oscillator and a full-wave bridge rectifier circuit. Moreover, the investigated circuits as well as the degradation behaviour under external loads during the operational lifetime in order to model the functionality are demonstrated.

A multiple system level modeling approach to coupled energy markets: Incentives for combined heat and power generation at the plant, city and regional energy system levels

The energy system can be subdivided into interconnected structural levels with differing boundary conditions and objectives. For heat and power generation, these levels may be the: electricity price area (regional); heat price area (city); and production site (power plant). This work presents a multi-system modeling approach for the analysis of investments and operation of combined heat and power (CHP) plants, as optimized on a regional, city, or production site energy system level. The modeling framework, comprising three energy system optimization models at the respective levels, is applied to a case study of Sweden, electricity price area SE3. The modeling levels are optimized separately but linked through electricity and heat prices. The results show that optimized CHP plant investments and operation on the three levels can both align and differ, depending on conditions. With a low biomass price and moderate congestion in transmission capacity into the city, the results from the three levels generally align. Differences arise if the biomass price is increased, which impacts the competitiveness of CHP plants in the region, while city-level CHP investments are mainly determined by the local heat demand and less-sensitive to external changes. The differences indicate a risk for diverging expectations between system levels.

A novel system-level modeling and design approach for high performance single-loop sigma-delta (∑Δ) modulators

PurposeThis paper attempted a novel approach for system-level modeling and simulation of sigma-delta modulator for low-frequency CMOS integrated analog to digital interfaces. Comparative analysis of various architectures topologies, circuit implementation techniques are described with analytical procedure for effective selection of topologies for targeted specifications.Design/methodology/approachVirtual instruments are presented in labview environment to analyze the correlation of circuit-level non-ideal effects with key design parameters over sampling ratio, coarse quantizer bits and loop filter order. A fourth-order single-loop sigma-delta modulator is designed and verified in MATLAB simulink environment with careful selection of integrator weights to meet stable desired performance.FindingsThe proposed designed achieved SNDR of 122 dB and 20 bit resolution satisfying high-resolution requirements of low-frequency biomedical signal processing applications. Even though the simulation performed at behavioral level, the results obtained are considered as accurate, by including all non-ideal and non-linear circuit errors in simulation process.Originality/valueVirtual instruments using labview environment used to analyze the correlation of circuit-level non-ideal effects with key design parameters over sampling ratio, coarse quantizer bits and loop filter order for accurate design.

Truck platooning in the U.S. national road network: A system-level modeling approach

Truck platooning enables a group of trucks to move close together, which helps reduce truck fuel use and increase effective road capacity. In this paper, a system-level equilibrium model is developed to characterize spontaneous truck platooning with coexistence of non-platooning vehicles in a network, by explicitly accounting for the interlocking relationship among platoon formation time, truck fuel saving, and increase in effective road capacity. To equilibrate the relationships, an algorithm is proposed which involves a diagonalization approach and a bush-based algorithm to solve decomposed subproblems. The condition of proportionality is imposed to obtain unique traffic flows for each class of vehicles on road links. In addition, a spatially constrained multivariate clustering technique is employed to construct origin/destination zones that are smaller than the coarse Freight Analysis Framework (FAF) zones, while maintaining reasonable computational burden for network traffic assignment. Model implementation in the U.S. shows that platooning could lead to 7.9% fuel saving among platoonable trucks in 2025 and a comparable increase in effective capacity of platoonable road links, which would account for 60% of rural interstate roads. The fuel saving and road capacity improvement translate into an annual cost reduction of $868 million for the U.S. intercity trucking sector and reduced road infrastructure investment needs worth $4.8 billion. Extensive sensitivity analysis further reveals that fuel saving of platoonable trucks increases with platoon size but decreases with inter-truck distance in a platoon. Fuel saving potential suggests that priority should be given to rural rather than urban roads in deploying platooning technologies. As expected, greater market penetration of platooning technologies means higher fuel saving and greater increase in effective road capacity.

Virtual design and optimization studies for industrial silicon microphones applying tailored system-level modeling**This work was carried out at the Technical University of Munich, Chair for Physics of Electrotechnology. Thomas Kuenzig is now with Infineon Technologies AG, Neubiberg.

Maxing out the technological limits in order to satisfy the customers’ demands and obtain the best performance of micro-devices and-systems is a challenge of today’s manufacturers. Dedicated system simulation is key to investigate the potential of device and system concepts in order to identify the best design w.r.t. the given requirements. We present a tailored, physics-based system-level modeling approach combining lumped with distributed models that provides detailed insight into the device and system operation at low computational expense. The resulting transparent, scalable (i.e. reusable) and modularly composed models explicitly contain the physical dependency on all relevant parameters, thus being well suited for dedicated investigation and optimization of MEMS devices and systems. This is demonstrated for an industrial capacitive silicon microphone. The performance of such microphones is determined by distributed effects like viscous damping and inhomogeneous capacitance variation across the membrane as well as by system-level phenomena like package-induced acoustic effects and the impact of the electronic circuitry for biasing and read-out. The here presented model covers all relevant figures of merit and, thus, enables to evaluate the optimization potential of silicon microphones towards high fidelity applications.

Cumulative energy demand and environmental impact in sustainable machining of inconel superalloy

Abstract Compared to flood machining, dry machining has sustainable potentials by eliminating the consumption of pump energy and coolant in production. However, the consumption of tool material with high embodied energy is significant in dry machining due to fast tool wear. Nevertheless, the trade-off on cumulative energy demand is not understood yet when considering the usage of materials, energy, and fluids. This study provides an innovative system-level modeling approach to assess the cumulative energy demand and environmental impact in machining of Inconel 718 as a function of energy consumption of machine tool and embodied energy consumption of work material, cutting tool, and coolant. The machine specific energy has been measured in dry and flood milling of Inconel 718. The relationship between specific cumulative energy demands and MRR has been investigated. The threshold MRR to differentiate cumulative energy demand of dry milling and flood milling has been determined. Dry milling has a smaller optimal process window for minimum cumulative energy demand than flood milling. The influence of embodied energy due to material consumption on machining sustainability is significant.

Reconfigurable Digital Channelizer Design Using Factored Markov Decision Processes

In this work, a novel digital channelizer design is developed through the use of a compact, system-level modeling approach. The model efficiently captures key properties of a digital channelizer system and its time-varying operation. The model applies powerful Markov Decision Process (MDP) techniques in new ways for design optimization of reconfigurable channelization processing. The result is a promising methodology for design and implementation of digital channelizers that adapt dynamically to changing use cases and stochastic environments while optimizing simultaneously for multiple conflicting performance goals. The method is used to employ an MDP to generate a runtime reconfiguration policy for a time-varying environment. Through extensive simulations, the robustness of the adaptation is demonstrated in comparison with the prior state of the art.

System architecture for functional characterization of devices to mitigate hearing impairment

Since 2000, claims of hearing loss by warfighters have doubled. It is the most frequently identified combat-related disability. Conventional audibility enhancement relies heavily on hearing aids, which do not provide sufficient sound intelligibility for a sizable subset of the hearing-impaired population. For them, there is a surgical option called a ‘cochlear implant’, a device which bypasses the damaged portions of the inner ear (cochlea) and provides direct neural stimulation. In this paper, we review the current state of the art in hearing aids and cochlear implants. A new device which has the potential for high spectral and temporal fidelity, the optical cochlear implant, is currently being tested in the laboratory. The projected development timeline spans many years: from point testing in the laboratory, through the approval process for limited human testing, with control gates for application to human candidates. A model-based development approach could potentially shorten this timeline. In this paper, we describe models and simulations that we developed to extend laboratory measurements in order to evaluate intelligibility impacts. Specifically, we describe our development of the Cochlear Laser Transduction Model, a physics-based simulator that evaluates tonotopic specificity; the Optical Cochlear Implant Simulator (OCIS), which can extend the laboratory measurements via simulation using the results of the Cochlear Laser Transduction Model; and the configuration of an off-the-shelf speech recognition tool to quickly assess intelligibility impacts, predicting system level impacts of varying optical cochlear implant design parameters. Results from the system-level modeling and simulation approach indicate that significant intelligibility improvements could be realized with the optical cochlear implant, with potential to offer upwards of 40 channels of spectral resolution compared with 10 channels with electrode-based implants.

System-level modeling for economic evaluation of geological CO2 storage in gas reservoirs

One way to reduce the effects of anthropogenic greenhouse gases on climate is to inject carbon dioxide (CO2) from industrial sources into deep geological formations such as brine aquifers or depleted oil or gas reservoirs. Research is being conducted to improve understanding of factors affecting particular aspects of geological CO2 storage (such as storage performance, storage capacity, and health, safety and environmental (HSE) issues) as well as to lower the cost of CO2 capture and related processes. However, there has been less emphasis to date on system-level analyses of geological CO2 storage that consider geological, economic, and environmental issues by linking detailed process models to representations of engineering components and associated economic models. The objective of this study is to develop a system-level model for geological CO2 storage, including CO2 capture and separation, compression, pipeline transportation to the storage site, and CO2 injection. Within our system model we are incorporating detailed reservoir simulations of CO2 injection into a gas reservoir and related enhanced production of methane. Potential leakage and associated environmental impacts are also considered. The platform for the system-level model is GoldSim [GoldSim User’s Guide. GoldSim Technology Group; 2006, http://www.goldsim.com]. The application of the system model focuses on evaluating the feasibility of carbon sequestration with enhanced gas recovery (CSEGR) in the Rio Vista region of California. The reservoir simulations are performed using a special module of the TOUGH2 simulator, EOS7C, for multicomponent gas mixtures of methane and CO2. Using a system-level modeling approach, the economic benefits of enhanced gas recovery can be directly weighed against the costs and benefits of CO2 injection.

Modeling of simultaneous switching noise in high speed systems

Simultaneous switching noise (SSN) has become a major bottleneck in high speed digital design. For future systems, modeling SSN can be complex: due to the thousands of interconnects that need to be analyzed. This is because a system level modeling approach is necessary that combines the chip, package and board level interactions. This paper presents an efficient method to model the SSN for high speed systems by developing circuit models for the planes and interconnections that can be combined using superposition theory. This approximation is valid at frequencies where skin effect is dominant. Simulation results are compared with the measurements on a test vehicle, verifying the validity of the method. In addition a system has been simulated to compute SSN, showing the application of this method for complex systems.