Study On Multilevel Hierarchical Control Of Vehicle Controller Of Series-Parrel Hybrid Forklift

In recent years benefited from the rapid development of new energy vehicles and responding to the requirements of national energy saving, hybrid forklift truck industry has now become a hot research topic. For the purpose of energy saving, well-known engineering machinery companies have been researching the hybrid truck. Further study of hybrid forklift can significantly improve fuel economy and reduce emissions.The background of the thesis is a series-parallel hybrid forklift R&D project. The structure and the main parameters of the vehicle were designed. Operating system is the most important feature between the hybrid forklift and vehicle. Referencing modeling hybrid cars and test data and vehicle parameters, the forward simulation model was constructed in Matlab/Simulink. The simulation model includes the driver, the power system, transmission system, vehicle dynamics and operating mechanism model.Energy management is the key technology. In this thesis, the vehicle controller was designed by the hierarchical intelligent control theory. The finite state machine theory was used to manage the energy flows for the complex operation mode of the vehicle. The simulation experiments and prototype testing were done in the certain conditions of the forklift cycle. The results show that the control strategy can meet the dynamic requirements of the truck and greatly improve the fuel economy.Finally, in order to further improve the series-parallel hybrid forklift fuel economy, the Particle Swarm Optimization was adopted to optimize control parameters of the vehicle controller. Optimization results show that optimal control parameters can be used to further improve fuel economy.