Research on the speed fluctuation control of diesel engine under load changes via an improved sparrow algorithm

Area of Science:

• Engineering
• Control Systems
• Automotive Engineering

Background:

• Diesel engine speed control presents challenges due to nonlinear and time-varying dynamics.
• Conventional Proportional-Integral-Derivative (PID) controllers exhibit limitations in managing system response lag and overshoot.
• Adapting to complex load changes is difficult for standard PID controllers.

Purpose of the Study:

• To enhance diesel engine speed control adaptability using a novel control strategy.
• To develop an improved sparrow search algorithm (ISSA) for optimizing controller parameters.
• To compare the performance of the proposed fuzzy PID (FPID) controller against traditional PID control.

Main Methods:

• An improved sparrow search algorithm (ISSA) was developed and validated using test functions for convergence and accuracy.
• The ISSA was employed to tune the parameters of a fuzzy proportional integral derivative (FPID) controller.
• Experimental comparisons were conducted between the FPID controller and a traditional PID controller under various operating conditions.

Main Results:

• The ISSA demonstrated accelerated convergence and increased accuracy compared to standard algorithms.
• The FPID controller reduced adjustment time by 1.4 seconds and overshoot by 6.8% at 2000 RPM.
• Under load changes (8 and 10), the FPID controller decreased stabilization duration by 18% and 30%, and fluctuation deviation by 7% and 12%, respectively.

Conclusions:

• The proposed FPID control strategy, optimized by ISSA, significantly improves diesel engine speed control performance.
• The FPID controller offers enhanced adaptability and stability, outperforming traditional PID controllers.
• This approach provides robust support for stable diesel engine operation during dynamic speed fluctuations.