Energy harvesting charger and battery state-of-charge indicator for low-power iot devices

다국어 초록 (Multilingual Abstract)

Advances in CMOS processes and low-power design techniques have led very low power Internet of Things (IoT) devices. Therefore, harvesting even a small amount of energy can provide a substitute for the batteries in such devices whose battery replacement is difficult. Furthermore, the battery capacity requirements for IoT devices have also been relaxed. At the same time, applications of IoT devices are becoming more varied, often requiring miniaturization of IoT sensor node systems. As a result, small-capacity, miniature IoT batteries are increasingly used by these IoT devices whose power is supplied by the energy harvesting.
A high-efficiency charger for low-power thermoelectric energy harvesting with a method for improving the efficiency, which is called the adaptive input ripple (AIR) maximum power point tracking (MPPT) technique, is introduced in this theses. On the basis of the key finding that the end-to-end efficiency (ηE-E) is highly dependent on the amplitude of the input ripple of the charger (ΔVIN) in the low-power region, the proposed AIR MPPT technique adjusts ΔVIN to maximize ηE-E. Moreover, the minimum input power that allows the charger to maintain operation is enhanced by the proposed AIR MPPT technique. The proposed charger is implemented with 180-nm CMOS technology. An improvement of 21% in ηE-E is achieved with the proposed technique. Furthermore, the proposed technique enhances the minimum power by 7.5 μW. The startup power and minimum power of the prototype are 37 and 6 μW, respectively. The maximum ηE-E is 82%.
An energy efficient State-of-Charge (SOC) indication algorithm and integrated system for low power wireless sensor nodes with the miniature IoT batteries are also introduced in this thesis. Based on the key findings that the miniature Li-ion batteries exhibit a fast response to the battery current transient, we propose an instantaneous linear extrapolation (ILE) algorithm and circuit system based on the ILE algorithm allowing accurate on-demand estimation of SOC. Due to the on-demand operation, an always-on current integration is avoided, reducing power and energy consumption by several orders of magnitude. Furthermore, the proposed SOC indicator does not require a battery disconnection from the load, ensuring continuous operation of the applications. The system is implemented in a 180-nm CMOS technology. The power consumption is 42 nW and maximum SOC indication error is 1.7%. The minimum applicable battery capacity is as low as 2 μAh.

목차 (Table of Contents)

• I. INTRODUCTION 10
• 1. Introduction and Background 10
• 2. Thesis Overview 14
• II. CONVENTIONAL WORKS 16
• 1. Energy Harvesting System for Thermoelectric Generator 16
• 1.A. Overall architecture of thermoelectric energy harvesting system 16
• 1.B. Thermoelectric generator and its modeling 17
• 1.C. Boost converter 19
• 1.D. Maximum Power Point Tracking (MPPT) 20
• 2. Battery State-of-Charge Indicator 21
• 2.A. Conventional method: Voltage relaxation method 21
• 2.B. Conventional method: Coulomb counting method 22
• III. A HIGH-EFFICIENCY CHARGER WITH ADAPTIVE INPUT RIPPLE MPPT FOR LOW-POWER ENERGY HARVESTING 24
• 1. Motivation 24
• 2. End-to-End, Charger and MPPT Efficiencies 27
• 3. Proposed System with Adaptive Input Ripple (AIR) MPPT Technique 29
• 4. Circuit Implementation 37
• 4.A. Top Architecture 37
• 4.B. AIR MPPT Controller 39
• 4.C. Low Power Starter 41
• 4.D. SHS Controller and Buffer 42
• 5. Measurement Results 45
• 6. Performance Summary 50
• IV. AN ULTRA-LOW POWER ON-DEMAND STATE-OF-CHARGE INDICATOR FOR MINIATURE IOT LI-ION BATTERIES 52
• 1. Motivation 52
• 2. On-Demand Direct EMF Calculation with Battery Current (IB) Modulation 55
• 3. Key Findings for Miniature IoT Batteries 58
• 3.A. Battery IB Transient Response 58
• 3.B. Battery Measurement Results 60
• 4. Proposed Instantaneous Linear Extrapolation (ILE) Algorithm 62
• 5. Circuit Implementation 64
• 5.A. Top Architecture 64
• 5.B. Adaptive Current Stabilizer (ACS) 67
• 5.C. Battery Current and Battery Voltage Sensors 77
• 6. Measurement Results 81
• 7. Performance Summary 89
• V. CONCLUSION 91
• BIBLIOGRAPHY 94