Flex-fuel vehicles play a crucial role in energy conservation and emission
reduction; however, they often rely on expensive fuel identification sensors at
the nozzle to accurately control the blending ratio. To reduce costs and enhance
engine flexibility, this paper presents a flexible fuel proportion
identification algorithm that utilizes exhaust oxygen content measured by the
oxygen sensor and engine air intake data. Additionally, the algorithm
incorporates air intake feedback control and λ feedback
control, which adjusts both the throttle opening and fuel mass of the flex-fuel
engine, ensuring optimal operating conditions at all times. A methanol-gasoline
flex-fuel engine model was developed using GT-Power, and the algorithm model was
implemented in Simulink software. Then, a co-simulation model of GT-Power and
Simulink is established. In the GT-Power engine model, three parameters—engine
speed, load, and methanol blending ratio—are set for the sweep points. The
algorithm model in Simulink calculates the methanol blending ratio based on the
data output from the GT-Power sweep points. Finally, the calculated blending
ratio is compared with the actual blending ratio set in GT-Power to verify the
accuracy of the algorithm described in this paper. Results indicate that the
error in the methanol blending ratio calculated by the algorithm is less than
2%. The algorithm presented in this paper utilizes real-time simulation
technology based on fully algebraic equations, resulting in high efficiency,
accuracy, and sensitivity.