Research on the Multi-Energy Management Strategy of the Electric Drive System of a Tracked Bulldozer

Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2016, Article ID 5631209, 13 pages http://dx.doi.org/10.1155/2016/5631209 Research Article Research on the Multi-Energy Management Strategy of the Electric Drive System of a Tracked Bulldozer Ming Pan, Jun Yan, Qunzhang Tu, and Chengming Jiang College of Field Engineering, PLA University of Science and Technology, Nanjing 210007, China Correspondence should be addressed to Qunzhang Tu; Received 10 October 2015; Accepted 14 February 2016 Academic Editor: Ivano Benedetti Copyright © 2016 Ming Pan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The multi-energy management strategy of electric drive system of tracked bulldozer was researched. Firstly, based on power requirement of typical working condition of a tracked bulldozer, the power distribution strategy for three energy sources in the front power chain was proposed by using wavelet theory and fuzzy control theory. Secondly, the electric drive system simulation platform was built in MATLAB/Simulink. At last, a driver-controller based HILS (hardware-in-the-loop simulation) platform was built and the multi-energy management strategy was verified. The HILS result shows that front power chain’s power output can meet the back power chain’s requirement, the engine-generator set works near the best fuel consumption curve, and the battery pack’s charge-discharge frequency and current are low. Thus the designed multi-energy management strategy can be used in real-time control of electric drive bulldozer. 1. Introduction Nowadays, energy saving and environmental protection have become more and more important [1]. In order to mitigate environmental issues caused by petroleum combustion [2], the electric drive technique has been widely used in areas such as automobile, engineering machinery, ship, and harbor hoisting machinery. As a key technology of electric drive system, the energy management strategy (EMS) has been studied extensively and deeply in order to improve the electric drive system’s performance. EMS used in electric system can be mainly divided into four kinds. (1) Rule-Based Logic Threshold Control Strategy. In [3], a rule-based strategy (RBS) for plug in hybrid electric vehicle (PHEV) was proposed. The PHEV operated in different modes which were determined by control rules designed based on state of charge (SOC) of the battery, power requirement, vehicle speed, and engine coolant temperature. Simulation results show that, with the proposed RBS energy management strategy, the gas mileage of the PHEV increased by 16% over the Prius control strategy. In [4], the regenerative braking strategy, used to distribute braking torque between electric braking system and mechanical braking system, was designed by setting switch thresholds of brake pedal travel and battery SOC. Although rule-based logic threshold control strategy is simple and practical, the setting of threshold relies too much on experience and experimental data, while the actual control effect is not good. (2) Fuzzy Logic Control Strategy. The basic idea of such strategy is to formulate a collection of fuzzy IF-THEN rules from human knowledge and reasoning, which offers a qualitative description of controlled system [2, 5]. Baumann et al. [6] and Lee and Sul [7] propose a fuzzy logic based torque control strategy for parallel HEVs in 1998. After that, the fuzzy control method was also used in series HEVs [8] and series-parallel HEVs [9]. In order to improve the performance of fuzzy controller, intelligent optimal algorithms such as GA [10], PSO [11], and BA [12] were adopted to optimize membership function and fuzzy rules. Furthermore, the adaptive neural fuzzy inference system (ANFIS) [13], machine learning algorithm [14], and 2 Mathematical Problems in Engineering General controller Sprocket Enginegenerator AC/DC Battery DC/DC Super capacitor DC/DC Front power chain DC bus Motor controller Motor Motor controller Motor Sprocket Back power chain CAN bus Electrical connection Mechanical connection Figure 1: Structure diagram of series electric drive system. driving cycle recognition [15, 16] were introduced to fuzzy control strategy. (3) Dynamic Program (DP). DP is a kind of mathematical method used to solve optimization problems which has been widely used in engineering fields. The main idea of DP is to divide the target optimization problem into several subproblems; then the global optimization solution of the target problem can be achieved by computing local optimal solution of subproblems. In [17], Koot combined traditional control method with DP and the fuel economy was improved by 3∼5%. In [18], the stochastic dynamic program method was proposed by Liu and Peng. Dynamic models of the hybrid electric drive system was built and the global optimization control strategy was designed. (4) Local Instantaneous Optimization Strategy. The output torque of the hybrid system was controlled in order to lower the equivalent fuel consumption. In [19, 20], the equivalent fuel consumption per hour was calculated by converting charging energy into fuel combustion of the engine. The simulation results show that the fuel efficiency of local instantaneous optimization strategy is better than the rulebased control strategy and it can be used in unknown driving condition. However, the calculation is very time-consuming and the real-time control of automobiles cannot be achieved by instantaneous optimization strategy. The application of electric drive technique in bulldozer is still in beginning stages; there is only one kind of electric drive bulldozer which is launched by Caterpillar Inc. at present. The relevant energy management strategy is rarely researched. The control strategy of bulldozer driving condition is similar to armored tracked vehicle which can be taken as a reference, but in bulldozing condition, the power requirement of the back power chain is quite different from automobile and armored vehicle. The control strategies mentioned above are not suitable for bulldozing condition, so that the multi-energy management in bulldozing condition is a difficult issue to resolve for electric drive dozer. The electric drive bulldozer contains 3 power sources: an engine-generator set, a battery pack, and a supercapacitor. The energy distribution strategy among these power sources determines the dynamic performance, fuel economy, and service life of critical components. Thus the multi-energy management strategy was built based on wavelet theory and fuzzy control theory. The strategy makes output and requirement of power meet when distributing output of the three power sources. Furthermore, the strategy also considers the effects of changing frequency of power requirement on engine-generator set, battery (...truncated)