Reinforcement Learning-Based Dynamic Power Management of a Battery-Powered System Supplying Multiple Active Modes

Abstract-This paper addresses the problem of extending battery service lifetime in a portable electronic system while maintaining an acceptable performance degradation level. The proposed dynamic power management (DPM) framework is based on model-free reinforcement learning (RL) technique. In this DPM framework, the Power Manager (PM) adapts the system operating mode to the actual battery state of charge. It uses RL technique to accurately define the optimal battery voltage threshold value and use it to specify the system active mode. In addition, the PM automatically adjusts the power management policy by learning the optimal timeout value. Moreover, the SoC and latency tradeoffs can be precisely controlled based on a userdefined parameter. Experiments show that the proposed method outperforms existing methods by 35% in terms of saving battery service lifetime. Keywords-Dynamic power management; reinforcement learning, extending battery lifetime; battery-powered system design

On battery recovery effect in wireless sensor nodes

With the perennial demand for longer runtime of battery-powered Wireless Sensor Nodes (WSNs), several techniques have been proposed to increase the battery runtime. One such class of techniques exploiting the battery recovery effect phenomenon claims that performing an intermittent discharge instead of a continuous discharge will increase the usable battery capacity. Several works in the areas of embedded systems and wireless sensor networks have assumed the existence of this recovery effect and proposed different power management techniques in the form of power supply architectures (multiple battery setup) and communication protocols (burst mode transmission) in order to exploit it. However, until now, a systematic experimental evaluation of the recovery effect has not been performed with real battery cells, using high accuracy battery testers to confirm the existence of this recovery phenomenon. In this paper, a systematic evaluation procedure is developed to verify the existence of this battery recovery effect. Using our evaluation procedure we investigated Alkaline, Nickel-Metal Hydride (NiMH) and Lithium-Ion (Li-Ion) battery chemistries, which are commonly used as power supplies for WSN applications. Our experimental results do not show any evidence of the aforementioned recovery effect in these battery chemistries. In particular, our results show a significant deviation from the stochastic battery models, which were used by many power management techniques. Therefore, the existing power management approaches that rely on this recovery effect do not hold in practice. Instead of a battery recovery effect, our experimental results show the existence of the rate capacity effect, which is the reduction of usable battery capacity with higher discharge power, to be the dominant electrochemical phenomenon that should be considered for maximizing the runtime of WSN applications. We outline power management techniques that minimize the rate capacity effect in order to obtain a higher energy output from the battery

Monitoração de tensão em equipamentos alimentados por bateria

Neste projeto é implementado um sistema de monitoração da tensão de bateria de equipamentos alimentados por essa fonte de energia. O objetivo principal deste projeto é disponibilizar uma leitura de fácil entendimento das condições da bateria, disponibilizado as informações em um display LCD. Desta forma, a verificação desta fonte de energia pode ser realizada em qualquer instante, sendo possível antever imprevistos. Para isto, é utilizado um microcontrolador PIC 16F876, programado em linguagem C e Assembler. A aplicação dos sinais é controlada pelo microntrolador. O microcontrolador monitora as informações da fonte de alimentação utilizada, medindo sua corrente, tensão e a quantidade de carga existente na fonte no momento exato da conexão ao dispositivo pelo usuário.Neste projeto é implementado um sistema de monitoração da tensão de bateria de equipamentos alimentados por essa fonte de energia. O objetivo principal deste projeto é disponibilizar uma leitura de fácil entendimento das condições da bateria, disponibilizado as informações em um display LCD. Desta forma, a verificação desta fonte de energia pode ser realizada em qualquer instante, sendo possível antever imprevistos. Para isto, é utilizado um microcontrolador PIC 16F876, programado em linguagem C e Assembler. A aplicação dos sinais é controlada pelo microntrolador. O microcontrolador monitora as informações da fonte de alimentação utilizada, medindo sua corrente, tensão e a quantidade de carga existente na fonte no momento exato da conexão ao dispositivo pelo usuário

Energy efficient scheduling techniques for real-time embedded systems

Battery-powered portable embedded systems have been widely used in many applications. These embedded systems have to concurrently perform a multitude of complex tasks under stringent time constraints. As these systems become more complex and incorporate more functionality, they became more power-hungry. Thus, reducing power consumption and extending battery lifespan while guaranteeing the timing constraints has became a critical aspect in designing such systems. This gives rise to three aspects of research: (i) Guaranteeing the execution of the hard real-time tasks by their deadlines, (ii) Determining the minimum voltage under which each task can be executed, and (iii) Techniques to take advantage of run-time variations in the execution times of tasks. In this research, we present techniques that address the above aspects in single and multi processor embedded systems. We study the performance of the proposed techniques on various benchmarks in terms of energy savings

Battery-Driven Dynamic Power Management

Battery lifetime extension is a primary design objective for portable systems. We introduce the concept of battery-driven dynamic power management, which strives to enhance lifetime by automatically adapting discharge rate and current profiles to battery charge state

Battery-Driven Dynamic Power Management of Portable Systems

Battery life-time extension is a primary design objective for portable systems. Traditionally, battery life-time has been prolonged mainly by reducing average power consumption of system components. A careful analysis of discharge characteristics and the adoption of accurate high-level battery models in system-level design open new opportunities for life-time extension. In this paper, we introduce dynamic power management (DPM) policies specifically tailored to battery-powered systems. Battery-driven DPM strives to enhance life-time by automatically adapting discharge rate and current profiles to battery state-of-charge. The distinctive feature of these policies is the control of system operation based on the observation of battery output voltage. The effectiveness of the proposed policies and, more in general, of the idea of accounting for battery behavior during system design, is proved by the experiments carried out on a realistic case study, namely, an MP3 audio player