Research Association of
Biomass Innovation
for Next Generation
Automobile Fuels

(raBit)

SCROLL

Objective

Contribute to realization of a sustainable, carbon-neutral society through innovations which create cellulosic ethanol by utilizing bio-resources.

Research
outline

- Toward a Carbon-Neutral Society -
Efficient Bioethanol Production leads
to low Carbon Intensity bioethanol

Overview

Production and research center
(Head office)
Date
founded
July 1st, 2022
Director general
Koichi Nakata(Toyota Motor Corporation )
Address
294-5 Nishidaira, Ogawara, Okuma-machi
Futaba-gun, Fukushima
Research activities
Research on establishing efficient cellulosic bioethanol production process
Homepage
https://rabit.or.jp/

Association Members

(order of the Japanese syllabary)

ENEOS Corporation, SUZUKI MOTOR CORPORATION, SUBARU CORPORATION,
Daihatsu Motor Co., Ltd., Toyota Motor Corporation, Toyota Tsusho Corporation
and Mazda Motor Corporation

Special Supporting Members

AISIN CORPORATION, DENSO CORPORATION and NIPPON STEEL ENGINEERING
CO., LTD.

Supporting Members

OHIKE Co., Ltd., KYOYEI CO.,LTD., KPP GROUP HOLDINGS CO., LTD.,
Shimadzu Corporation, Chubu Electric Power Co., Inc., MARUYASU INDUSTRIES
CO., LTD., merkmal Co., LTD. and Yamaha Motor Co., Ltd.

Our
Research

SCROLL

01

Research on efficient production systems for ethanol

This study aims to enhance cellulosic ethanol production technologies using non-food biomass by operating dedicated research facilities. It focuses on identifying and addressing production challenges across various feedstocks, while improving overall system efficiency.

02

Research on the recovery and utilization of byproduct oxygen and CO2.

The effective utilization of high-purity oxygen generated during hydrogen production and CO2 emitted during Cellulosic ethanol fermentation.

03

Research on efficient operational methods for the entire system including fuel utilization.

To identify challenges in the use of bioethanol for vehicles and explores potential solutions. It also proposes a predictive model to estimate fuel output based on raw material cultivation yields.