Due to the rising concern about environmental effects and cost onboard, various scenarios including the use of clean fuels, renewable energies, and the optimization of power architectures have been proposed for green marine propulsions. As a midterm goal, the natural gas has been widely considered to achieve low CO₂ and zero SO_X pollutions. Meanwhile, renewable energies such as PV solar, wind have been introduced and coupled with energy storage systems to share the loads and provide assisted propulsion during the voyages. Considering the variable load and power features of natural gas fueled engines, the dual fuel engines have been used to drive the propeller directly, and the pure gas engines are mainly used to serve as generators.

The combination of gas engines and renewable energies has huge potential to reduce emissions over the whole life cycle in theory. However, the physical characteristics of new components and their control systems take uncertainty into the power systems in practice which requires more experimental investigations. Due to the scavenging efficiency and the time delay of turbochargers, as well as the low flame propagating velocity of natural gas, the transient load response of gas engines is weak, which may lead to an unsteady engine speed. In addition, the features of electronic components between renewable energy sources and power grids also cause the system property of low inertia, which may lead to fluctuations in the grid frequency. The electrification of the propulsion controls system and the diversification of power energies influences non-linearly the dynamic performance of the power systems.

As a result, improvements in the dynamic performance of power systems were conducted. From the point of view of gas engines, the optimization of structure and control methods of pre-chamber, valve timing, and turbochargers were explored to enhance the intake efficiency and accelerate the burning rate. On the side of the system level, operation condition control of ICE and power management including load distribution of batteries and supercapacitors were presented to accommodate the load response performance of gas engines. At the same time, the system-level real machine tests are of great importance and urgent to verify the credibility of simulations and to explore the mechanisms behind complex dynamic phenomena. Unfortunately, they are limited by the physical dimensions and costs of such a large-scale testbench.

This paper provides a review of the research on gas engine power electric systems onboard from literature. Aiming at the whole power system, many studies were conducted to predict the steady performance including the energy efficiency, reliability, electric quality as well as the power management strategies of gas-electric powertrains by simulations and small-scale physical platforms. However, the simulations and experiments on the load response and emissions during the transient operations of these power systems are fairly limited. Considering the differently on system tests and the lack of experimental results, scaling methods such as the similarity theory and Willans-Line model are developed to establish the relationship for different size systems. In addition, this paper summarized the theories and the state-of-the-art works of scaled model tests and simulation for marine gas engine power systems, and the boundary of the scaled model experiments for such power applications via the similarity theory was discussed.

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To fully utilize the limited battery energy of mobile electronic devices, we propose an adaptive adjustment method of processing quality for multiple image stream tasks running with widely varying execution times. This adjustment method completes the worst-case executions of the tasks with a given budget of energy, and maximizes the total reward value of processing quality obtained during their executions by exploiting the probability distribution of task execution times. The proposed method derives the maximum reward value for the tasks being executable with arbitrary processing quality, and near maximum value for the tasks being executable with a finite number of processing qualities. Our evaluation on a prototype system shows that the proposed method achieves larger reward values, by up to 57%, than the previous method.

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Distributed power delivery is blooming in SoC power system because the fine-grained power management needs separate power sources to adjust each voltage island dynamically. In addition, dedicated power sources for critical circuit blocks can achieve better signal integrity. To extensively utilize the power modules when they are redundant and idle, this work applies the cooperation concept in SoC power management. The key controller is a mixed-signal estimator that executes the intelligent procedures, like real-time swap the power module depending on its loading and healthy condition, automatically configure the power system with phase interleaving, and support all the peripheral functions. To demonstrate the proposed concept, a prototype chip for voltage down-conversion is implemented. This chip contains four switched-inductor converter modules to emulate the cooperative power network. Each module is small therefore the power efficiency is not optimal for the heavy load. With the cooperation between power modules, the power efficiency is 88% for 300mA load, that is 8.5% higher than the single module operation.

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