Multi-Sensor Fusion for Low-Cost, Automated Woodstoves

EPA Grant Number: SU839466
Title: Multi-Sensor Fusion for Low-Cost, Automated Woodstoves
Investigators: Venkatadriagaram, Sundararajan , Vangrin, Robert Z , Rodriguez, Alexandra , Iverson, Denton , Orduna, Gabriel , Valencia, Jeanette , Lechiara, Matt , Patil, Ronak , Wishner, Ryan
Current Investigators: Venkatadriagaram, Sundararajan , Lechiara, Matt , Vangrin, Robert Z , Patil, Ronak , Iverson, Denton , Orduna, Gabriel , Wishner, Ryan , Valencia, Jeanette , Rodriguez, Alexandra
Institution: University of California-Riverside
EPA Project Officer: Callan, Richard
Phase: I
Project Period: December 1, 2018 through November 30, 2019 (Extended to November 30, 2020)
Project Amount: $14,753
RFA: P3 Awards: A National Student Design Competition Focusing on People, Prosperity and the Planet (2018) RFA Text |  Recipients Lists
Research Category: P3 Challenge Area - Air Quality , P3 Awards


This research aims to develop simple and inexpensive technology to reduce the levels of indoor and outdoor air pollutants generated by woodstoves in disadvantaged communities and rural areas. An additional goal is to increase efficiency of the woodstoves defined as the heat output per unit of fuel burned. A further goal is to experiment with lower-grade fuel in order to reduce fuel costs. The intended users of this woodstove are low-income households in cold climates of the United States, particularly Native American communities. The research adopts a multi-sensor fusion approach for the monitoring and control of automated woodstoves to make them more efficient, non-polluting and inexpensive.


The woodstove has two chambers - one for the main combustion and another for drying the wood prior to combustion. The combustion chamber employs primary air for the main combustion and pre-heated secondary air to assist in secondary combustion of the particulate matter. The drying chamber uses waste heat from the flue gases to drive out moisture in the wood; this reduces energy loss from evaporation when the wood is burned. This will allow the wood stove to operate at higher flame temperatures and will lead more complete combustion of the fuel with attendant reduction in carbon monoxide and particulate matter. The amount of excess air and the path of air are controlled to increase residence time to complete combustion and to extract as much energy as possible from the flue gases.

The woodstove will be equipped with sensors to monitor operating parameters such as air-flow, humidity, moisture, oxygen, particulate matter (PM) and carbon monoxide (CO) emissions and also environmental parameters such as humidity, wind speed and temperature. The data from these sensors will be gathered using an embedded platform and fused using signal processing, statistical methods and machine learning approaches to determine optimal control parameters such as air-flow for the main combustion and the pre-drying of the fuel. The controllers aims to extend the life of the fuel for a given amount of heating and to reduce both indoor and outdoor CO and PM emissions to beyond EPA requirements. This research will result in greater understanding of the interplay between the control variables, operating parameters and environmental conditions in the emissions and efficiency of woodstoves. It will also identify the significant parameters that need to be monitored and controlled under a range of conditions to achieve high efficiency and low emissions.

The project aims to reduce the indoor and outdoor particulate matter and carbon monoxide emissions in low-income communities. Current woodstoves are significant contributors to black carbon emissions. By reducing these emissions to beyond EPA standards, the project improves indoor and outdoor air quality. This leads to better respiratory health, especially for women, children and seniors who are likely to be indoors for significant portions of the day. The project also promotes efficient burning of wood, thereby helping low-income users avoid the cost of more expensive heating alternatives such as natural gas or oil. It will also deliver better emission and efficiency performance at lower costs to these communities.

The P3 project will be used in problem-based learning in three Mechanical Engineering classes and two Environmental Engineering classes at UC Riverside. The project will also be used to provide a bridge between the Sustainability Program by the Department of Gender and Sexuality Studies at UC Riverside and the College of Engineering. The project aims to include end-user and community input throughout the problem definition, design, fabrication and testing phases of the project. This approach will enable the dissemination of the project findings and methods to the end-users.

Expected Results:

The woodstove will supply a low-cost heating system to rural or low-income families who may not have easy access to other inexpensive fuel. The expected outcomes of the project are an automated wood-stove that 1) maintains the PM2.5 emissions less than 2.0 g/hr using crib-wood or 2.5 g/hr for cord-wood, 2) increases combustion efficiency beyond 80% and 3) costs less than $1000.

Contribution to Pollution Prevention or Control: The project will lead to reduction in indoor and outdoor PM2.5 and CO emissions from woodstove

Publications and Presentations:

Publications have been submitted on this project: View all 1 publications for this project

Supplemental Keywords:

exposure, health effects, indoor air, environmental justice, emission control technologies, sustainable development, clean technologies, innovative technology, engineering, modeling

Progress and Final Reports:

  • 2019 Progress Report