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The dynamic response of fuel injectors plays a key role in determining injection accuracy, fuel atomization quality, and engine combustion stability. During high-speed operation, injectors are required to open and close within a very short time, making their dynamic behavior difficult to analyze using experimental methods alone. To address this challenge, a co-simulation method combining AMESim and MATLAB is widely used to study injector dynamic response in a more efficient and flexible manner.

AMESim is well suited for modeling physical systems involving hydraulics, mechanics, and electromagnetics. In injector simulation, AMESim can accurately describe fuel flow characteristics, valve motion, and pressure dynamics inside the injector. By building a detailed injector model, including the electromagnetic actuator, control valve, and fuel chamber, the opening and closing process of the injector can be simulated under different operating conditions.

MATLAB, on the other hand, is mainly used for signal processing, control algorithm design, and data analysis. In the co-simulation framework, MATLAB is responsible for generating the injector driving signals, such as current or voltage waveforms. These signals are then transmitted to the AMESim injector model in real time. AMESim calculates the corresponding physical response of the injector and returns key outputs, including needle lift, injection pressure, and fuel flow rate, back to MATLAB for further analysis.

The interaction between AMESim and MATLAB allows researchers to study the influence of control strategies on injector dynamic response. For example, different current rise rates, peak currents, and holding currents can be easily tested in MATLAB without modifying the physical model in AMESim. This greatly improves simulation efficiency and supports rapid optimization of injector control parameters.

In addition, the co-simulation approach helps identify delays, oscillations, and response nonlinearities in the injector system. By comparing simulation results with experimental data, model accuracy can be gradually improved. This method also reduces the cost and time required for prototype testing.

In conclusion, the AMESim–MATLAB co-simulation method provides a practical and effective way to analyze injector dynamic response. By combining detailed physical modeling with flexible control design, this approach supports injector performance optimization and contributes to the development of advanced fuel injection systems.