NZE IoT Power Management via Segmented PMU and Charge Qualification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Net-zero energy (NZE) IoT devices face challenges in power management due to their small size, low cost, and complex computations, leading to inefficient energy harvesting and potential wastage during wake events, as they often require long deep sleep periods to replenish charge, making it meaningless to wake up if there is not enough charge to service tasks.
Innovation Solution
An always-on reconfigurable and lightweight hardware power management unit (PMU) that controls system power states based on current charge state, implementing voltage-based battery monitoring and energy qualification for asynchronous events, allowing robust operation across various power states and reducing power consumption during sleep and harvesting states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the device enters deep sleep state to replenish charge, then energy harvesting efficiency is improved, but the device cannot respond timely to wake events
Solution Approach 1:
The patent segments the power management unit into two parts: an always-on PMU that remains active during deep sleep to monitor charge and manage wake events, and the compute system that enters deep sleep to conserve energy. This segmentation allows the PMU to maintain awareness of wake events while the compute system saves power, resolving the contradiction between energy efficiency and response time.
Solution Approach 2:
The PMU performs preliminary actions by pre-monitoring charge levels and pre-qualifying wake events before the compute system needs to wake up. The PMU maintains a queue of qualified wake events and their associated charge requirements, so when the compute system wakes, the PMU can immediately provide the necessary information without requiring the compute system to re-evaluate everything from scratch, thus reducing wake-up response time.
2Productivity
If the device wakes up to service tasks, then task execution capability is improved, but power consumption increases
Solution Approach 1:
The PMU performs preliminary qualification of wake events against current charge levels before the compute system wakes up. By pre-determining which wake events are feasible given the current charge state, the system avoids waking up for tasks that cannot be completed, thereby reducing unnecessary power consumption while maintaining the ability to execute viable tasks.
Solution Approach 2:
The PMU continuously monitors charge levels and provides feedback to the compute system about power availability. This feedback mechanism allows the compute system to make informed decisions about which tasks to execute and when to wake up, optimizing the balance between task execution capability and power consumption by only waking up when sufficient charge is available.
3Adaptability or versatility
If the device uses firmware for power management control, then flexibility is improved, but device complexity increases
Solution Approach 1:
The patent segments power management control into two parts: a simple, always-on hardware PMU that handles basic power state transitions and charge monitoring, and a flexible compute system that can configure the PMU through software. This segmentation maintains flexibility in power management strategies while reducing the complexity burden on the compute system, as the PMU handles the complex real-time power state management hardware-wise.
Solution Approach 2:
The PMU acts as an intermediary between the compute system and the power management hardware. It provides a simplified interface that translates high-level power management requests from the compute system into concrete hardware actions. This intermediary approach maintains the flexibility needed for various power management strategies while shielding the compute system from the complexity of direct hardware control.
4Productivity
If the device performs complex computations, then processing capability is improved, but energy harvesting becomes insufficient
Solution Approach 1:
The PMU performs preliminary assessment of charge levels and wake event requirements before the compute system executes tasks. By pre-qualifying wake events and assessing whether sufficient charge is available for the intended computations, the system can prevent execution of tasks that would deplete the energy supply, thereby maintaining energy harvesting sufficiency while still enabling complex computations when energy is available.
Solution Approach 2:
The system dynamically adjusts its operational state based on real-time charge levels and task requirements. The PMU continuously monitors charge and can dynamically modify power state transitions, task selection, and execution timing to match the energy harvesting capabilities with computational demands, allowing the system to adapt between high-performance computation modes and energy-conservation modes as needed.
Data Source
AI summary
The present disclosure provides for the management of power of a NZE IoT device. Managing power can include receiving the one or more asynchronous events from the asynchronous event system, determining if any of the one or more asynchronous events meet a respective charge qualification, generating the power-on command for the power-managed compute system if any of the one or more asynchronous events meet the respective charge qualification, and waiting for a power source to reach a threshold associated with the respective charge qualification if any of the one or more asynchronous events do not meet the respective charge qualification.