Recipient Organization
TAKACHAR LIMITED
21 DRYDOCK AVENUE SUITE 610E
BOSTON,MA 022104501
Performing Department
(N/A)
Non Technical Summary
Most biomass (crop and forest) residues are loose, wet, and bulky, making them logistically costly to collect and convert into useful biofuel/bioproducts. As such, in Western States such as California, excess woody residues either are burned in prescribed fires, or cost landowners tremendously to move out of wildfire-prone regions. Takachar is developing small-scale, low-cost, portable equipment that can be latched onto the back of pick-up trucks to deploy to remote, hard-to-access landings and vegetation management operations to locally densify/upgrade the woody biomass into higher-value biofuels and bioproducts before transportation. As more equivalent energy or value can be now packed onto the same truckload compared to moving raw biomass, this saves electrical utilities hundreds of millions of dollars in vegetation management. This project will validate a feedstock-robust control system over a wide range of input biomass characteristics, consistently producing a biofuel of a heating value specified by a prospective customer despite the input fluctuations. If successful, this project will lead to an integrated hardware-software system that allows Takachar to scale our operation to different vegetation management operations with different biomass types and moisture contents, producing different user-specified bioproducts on demand. When commercialized in the beachhead market, we can help landowner expand vegetation management, increase biomass utilization, and reduce wildfire risk, thereby helping state and federal governments avert wildfire damages and suppression costs, avoiding carbon emissions, and creating additional livelihood in rural, underserved communities.
Animal Health Component
0%
Research Effort Categories
Basic
0%
Applied
100%
Developmental
0%
Goals / Objectives
Takachar is commercializing a torrefaction process developed at Massachusetts Institute of Technology (MIT) under low-oxygen (non-inert) conditions. In contrast to traditional torrefaction technologies, which often impose an inert atmosphere condition that is expensive and complicated to maintain, our work leads to a new class of simplified, continuous torrefaction reactor designs that are small-scale, low-cost, portable, and autothermal (does not require external energy source to start or operate). The technology also exhibits no open flames, which is an important requirement. The significance is that this work decentralizes deployment of torrefaction in remote, off-grid areas, allowing for production of densified, well-tempered bio-based products or their precursors at source. This output can be more affordably transported, in contrast with moving raw biomass, to end users. Furthermore, decentralized deployment of biomass torrefaction technology realizes, for the first time, the ability for raw biomass to be upgraded to user-specified characteristics in situ before transportation even begins. In order to achieve this with biomass that is highly variable in moisture, particle sizes, etc., we are developing a real-time, automated control system that is integral to the hardware. Based on existing lab validation, this proposal will specifically develop the control aspect, including the appropriate real-time monitoring and data processing capability to produce the desired quality-controlled output characteristics from variable input conditions. If successful, the knowledge and techniques developed in this work is not limited only to small-scale, decentralized biomass torrefaction. It can also be more broadly applied to other biomass conversion reactors such as gasification and biochemical processes, at small or large scales.In terms of hardware, we have demonstrated, in the lab, that our prototype can stably process a diverse range of input feedstock, with different particle geometries, sizes, and relative bulk porosities/densities. We have successfully experimented with incoming moisture contents ranging from 10-50%, though not yet in a systematic manner. We have obtained interest and even funding commitment from the prospective partners for demonstration. However, what these partners would like to see first is a validated automated control system.In terms of developing the control strategy, we have demonstrated in our lab-scale prototype that, by adjusting the air-to-biomass ratio, we can control the steady-state temperature. And by adjusting the output removal rate, we can control the solid residence time. The combination of these two variables gives us a robust handle on the reactor condition and on the output characteristics as a function of the input. We filed the appropriate patent application on this control strategy. We implemented a simple logic loop (first in Arduino and then in IFM) to automate the process at a lab scale. Yet, in order to develop this into a product that can be field-tested, we need to elaborate upon this controller logic over a wider range of more realistically variable input conditions, applying simple machine learning techniques to ensure that quality-controlled output is consistently met (for example, fixed carbon content, ash content). This missing technical milestone is required for our process to be useful to end users, and will be the subject of this project.
Project Methods
The work plan will consist of two parts. The first part will involve running different batches of input biomass prepared at specified, well-controlled moisture contents and particle size distributions, varying the reaction conditions, and mapping the output feedstock characteristics as a function of the reaction conditions and input biomass characteristics. This will produce data tables that will provide a science-based approach for undertaking the second part of the work plan. In the second part, we will allow the input biomass characteristics (moisture content, etc.) to fluctuate in a field-like condition. By fixing a desired output feedstock characteristic value, we will build an active control system to manipulate the reaction conditions in real-time to reliably deliver this fixed output value in spite of the fluctuating input biomass conditions.