Improved particle swarm optimization fuzzy PID fuel cell temperature control method

Abstract

The invention discloses an improved particle swarm optimization fuzzy PID fuel cell temperature control method. The method comprises the following steps: establishing a fuel cell dynamic model based on an MATLAB / Simulink simulation platform, and obtaining output power and corresponding temperature of a fuel cell through the fuel cell dynamic model; designing a fuzzy PID temperature controller forthe fuel cell dynamic model, and controlling an error and an error change rate of an expected temperature value and an actual temperature value by using the controller to obtain a parameter adjustmentamount of the fuzzy PID temperature controller; optimizing a quantization factor and a scaling factor in the fuzzy PID temperature controller by adopting an improved particle swarm algorithm; and assigning the optimized quantization factor and scaling factor to a fuzzy PID temperature controller so as to control the temperature of the fuel cell in real time. According to the method, improved particle swarm optimization fuzzy PID control is utilized, a control strategy is set according to a control experience rule, the method has the advantages of being high in robustness, high in response speed and the like, and it is ensured that the PEMFC stack is maintained at a fixed temperature.

Description

technical field [0001] The invention belongs to the technical field of fuel cell thermal management, in particular to an improved particle swarm optimization fuzzy PID fuel cell temperature control method. Background technique [0002] As the energy crisis and environmental pollution become more and more serious, the development of high-efficiency and low-pollution energy technology has become one of the major issues of all countries in the world. As a highly efficient and clean energy conversion device, fuel cells have received widespread attention in the automotive industry. Among them, the proton exchange membrane fuel cell (PEMFC) has the advantages of low operating temperature, fast start-up speed, high power generation efficiency, and mature technology, and has attracted more and more attention. [0003] Temperature has a significant impact on the performance and reliability of fuel cell systems. An increase in the temperature of the stack will increase the electroch...

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Problems solved by technology

[0004] At present, the most widely used is the classic PID control. The three parameters K of the traditional PID controller P , K I , K D is fixed, the parameter setting method is more cumbersome, and the system control is more difficult; the fuzzy control has good control performance, but the fuzzy PID controller also has shortcomings, the determination of quantization and proportional factors, the selection of the membership function and the formulation of the fuzzy rule table are very important. The control effect has an important influence, but it can only be obtained by relying on expert experience and engineering experience, and the interference caused by special conditions cannot be avoided, and the self-adaptive ability and control effect are not ideal

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