For the control of the working point switching process of the extended-range auxiliary power unit (APU)

a dynamic control strategy for the extended-range APU was proposed by using the chaotic annealing hybrid particle swarm optimization (CAHPSO) algorithm to optimize the fuzzy proportional-integral-derivative (PID) control. This algorithm was used to combine chaos search and annealing mechanisms based on the standard particle swarm optimization (PSO) to enhance the global optimization ability

and optimize the fuzzy PID control parameters offline. In order to verify the effectiveness of the new control strategy

the APU system simulation model was established. The simulation results showed that during the processes of gradually switching from the warming-up point to the high load point

the new control strategy can make the APU shorten the stabilization time

the stabilization time for the three switching control processes of the working points was 2.92 s

2.88 s

2.79 s

respectively; the new control strategy can make the APU reduce the speed overshoot rate

only when in the switching from the small load point to the middle load point

the speed overshoot rate was about 0.95% and there was no overshoot in other switching processes; the new control strategy can make the APU torque change smoothly

and the torque overshoot was only 0.16 N·m when switching from the middle load point to the high load point

which achieved a good dynamic control effect.