Study On The Energy Management System Of Hybrid Excavator

Hybrid technology is an effective way to reduce the fuel consumption and exhaust emissions of traditional excavators. The research on energy management system for hybrid excavators is of great significance to reduce the fuel consumption and emission of excavators and can be used for other types of hybrid construction machinery.For the hybrid excavator, the energy management system and energy flow have changed greatly, because of the addition of electric auxiliary drive system, electric swing system and the boom energy recovery system. Therefore, a deep research of hybrid excavator energy management system is needed, in order to develop an appropriate energy management strategy.The energy management strategy can improve the fuel economy, while ensuring the energy balance of energy storage system. In this thesis, the' energy management system of the hybrid excavator is studied based on the energy saving requirements. The main contents are as follows:the energy flow of the hybrid excavator is analyzed and the design requirements of the energy management strategy are obtained. Based on the characteristics of multi-input, multi-output,non-linear and conditional constraint of the energy management system of hybrid excavator, the energy system of the hybrid excavator is modeled, and the mathematical expression of the energy management problem is given. In order to solve this energy management problem,the optimal offline energy management strategy is obtained by numerical dynamic programming algorithm. The optimal control law can be summarized, and it can be used for development of online energy management strategy. In order to solve the problem that dynamic programming cannot be applied to online control, the analytic solution of the energy management problem is obtained by applying the Pontryagin's minimum principle. Based on this result, an online adaptive energy management with online updating, SOC feedback control and energy recovery compensation is proposed. Based on the cyclical characteristics of the typical operating cycles of excavator, the energy management strategy under typical operating cycles is proposed, which can further improve the fuel economy of the system. The proposed energy management strategy can improve the fuel economy of the system and also ensure the energy balance of the energy storage system. It can also help to promote the application and development of the hybrid excavator.The chapters of the thesis are as follows:In Chapter 1, the significance of the research on the energy management system of the hybrid excavator under the background of energy crisis and environmental pollution is discussed. The current research situation of the energy management strategy of the hybrid system is summarized. The energy management of the hybrid electric vehicle is analyzed. The research status of energy management strategy of hybrid electric vehicles is introduced. In view of the complicated structure and work cycles of construction machinery, the research status of energy management strategy of hybrid construction machinery, especially hybrid excavator. The difference between excavator energy management system and automobile system is also presented, and the existing problems in this research are analyzed.In Chapter 2, the energy management system of hybrid excavator is generally studied. The structures and working conditions of the hybrid excavator are studied, and the characteristics and energy saving potential of the hybrid excavator energy system are analyzed. Based on this,the energy flow analysis of the hybrid excavator is carried out, and the objectives and design requirements of the energy management strategy of the hybrid excavator are summarized.Based on the energy system model, the mathematical expression of energy management problem is given, and the energy management problem is regarded as a nonlinear and finite time optimization problem with constraints.In Chapter 3, the hybrid excavator energy management problem is solved using dynamic programing. The problem of energy management presented in Chapter 2 is discretized, and the problems of interpolation, discrete interval and state constraint encountered in the discretion process are discussed. Then the numerical dynamic programming algorithm is used to solve the energy management problem. Compared with the traditional excavator, the mechanism of energy saving of the hybrid excavator is obtained, and the energy saving ratio of each factor is obtained. By comparing with the rule-based energy management strategy, some control rules are obtained.In Chapter 4, the online energy management strategy is studied. An online adaptive energy management strategy is proposed. In the design process of the strategy, the minimum principle is used to solve the simplified energy management problem, and the general control law is deduced according to the analytical solution. Then, the electrical efficiency,energy recovery and state constraints of the energy management problem are considered. Finally, develop the online energy management strategy. Since the optimal control theory is applied in the design process, the strategy has a certain theoretical basis and can guarantee certain optimality. In this strategy, the initial factor is selected according to the excavator operation mode and is updated online according to the historical load information. The factor is also adjusted in real time according to the state value of the SOC, in order to meet the state constraint requirement. In energy recovery case the SOC changes dramatically. Therefore, the energy recovery compensation control is introduced. The simulation and experimental results show that the online energy management strategy can effectively improve the fuel economy of the hybrid excavator, and can be applied to various working conditions.In Chapter 5, the energy management strategy under typical operating cycles is studied.The hybrid excavator has the characteristics of cyclic operation under typical operating cycles,and this feature can be used to develop the energy management strategy for specific operating cycles, and further improve the fuel economy of the system. This chapter presents an energy management strategy based on reinforcement learning used for typical operating cycles. The load power is regarded as a stochastic state variable of the system, and the energy management problem of the hybrid excavator is regarded as a Markov decision process. The result of reinforcement learning algorithm is a time-independent energy management strategy. It can be directly applied to online control. Simulation and experimental results show that the proposed energy management strategy can achieve better fuel economy than the online adaptive energy management strategy under typical operating cycles. At the same time the strategy can be applied to operating cycles of the same work tasks.In Chapter 6, a design method for the power system of the hybrid excavator based on energy management is proposed. This method combines the optimal design of power system with energy management problem so that the power system can achieve the best both in terms of component cost and fuel consumption. Compared with the traditional design method which only considers the load power demand, this method takes into account the factors such as fuel economy, component cost, load power demand and operating conditions. The design results show that the proposed optimization design method can balance the fuel economy and component cost while guarantee the working efficiency, so it is more suitable for the design of the hybrid excavator power system. Another contribution of the study is to summarize the design rules of the excavator power system by introducing the concept of 'engine efficient operating point'. Using this design rule, the design time of the proposed design method can be reduced.In Chapter 7, the main conclusions and achievements are summarized and further research work is prospected.