**5. Results and Discussion**

Due to the lack of a standard drive cycle of bulldozers like that of automobiles, a representative actual drive cycle of the bulldozer, which was extracted and constructed from a large number of bulldozing experimental data in our previous research [7], was adopted for simulation and comparison. Figure 15 shows the drive cycle, including the bulldozing stage and empty returning stage. The bulldozing stage can be further divided into cutting-soil, transporting-soil, and unloading-soil stages.

**Figure 15.** Traction and speed of a representative actual drive cycle.

In order to validate and compare the control effect, three control strategies were compared under the representative actual drive cycle. Table 4 describes the compared strategies: a power following strategy in a preliminarily practical application (PF1), a typical power following strategy based on the engine minimum fuel consumption curve (PF2), and the proposed strategy (ASPF). Figure 16, Figure 17, Figure 18 and Table 5 show the comparison results.


**Table 4.** Comparison of different control strategies.



FC: fuel consumption; EFC: equivalent fuel consumption; EFSR: equivalent fuel saving rate.

**Figure 16.** Comparison of operating parameters of key powertrain components.

**Figure 17.** Distribution of engine working points. FC: fuel consumption, ηeg,bst: the best efficiency of the genset.

**Figure 18.** Distribution of generator working points.

Figure 16 shows the comparison of a group of key powertrain parameters, including the generator output power *P*g, supercapacitor output power *P*sc, supercapacitor *SOC*, engine torque *T*e, and engine speed *n*e. It can be observed that the generator output power fiercely fluctuates and follows the demand power under the PF1 and PF2. However, the change of generator output power is relatively smooth under the ASPF. The supercapacitor power under the ASPF is larger and fluctuates more than that under the PF1 and PF2. Meanwhile, the *SOC* of the ASPF varies within a permissible range. The first three subgraphs of Figure 16 illustrate that the self-adaptive filter algorithm in the ASPF can smoothen the power adaptively and keep the *SOC* within pre-set limits simultaneously by timely adjustment of the filter coefficient, which can prompt higher engagement and take full advantage of the high efficiency of the supercapacitor. The fourth and fifth subgraphs show that ASPF makes the engine speed and torque more stable, especially relative to the PF2 based on the trajectory, through smoothing the genset output power. Therefore, the ASPF can play a positive role in stabilizing the working points of the engine and generator, which can achieve a reduction of the transient energy loss.

Figure 17 compares the engine working points with different strategies under the same representative drive cycle. It can be seen that the engine working point distribution with PF1 is widespread and mainly within the speed range from 1300 to 1800 r/min in different loads, whereas it is far away from the low fuel consumption area. From the middle subgraph, we can see that the engine operating points of PF2 are distributed around the minimum fuel consumption curve. However, they could not coincide with the curve because of their dramatic fluctuation and insufficient response on the timeline shown in Figure 16. The left subgraph shows that the engine working point distribution of ASPF is very close to the pre-set optimal efficiency curves of combining the engine with the generator under different hydraulic pump consumed torque. This relatively concentrated distribution is the result of the effect of the adaptive filter link shown in the above graph.

Figure 18 compares the generator working point distribution with three control strategies under the same drive cycle. It can be seen that the distribution shape of the generator points is similar to that of the engine points on account of the coaxial junction of the engine and the generator. The generator working points of PF1 and PF2 are more widely distributed than those of ASPF for the adaptive filter. The difference between the generator torque below and the engine torque above is the hydraulic pump consumed torque, which is also reflected on the joint optimal efficiency curves in the above and below graphs. The ASPF keeps the generator points along the optimal efficiency curves as much as possible, in which following the routes can result in a greater generator efficiency.

The fuel consumption of the three control strategies and the prototype of the traditional hydro-mechanical bulldozer (HMB) under the same simulated drive cycle is shown in Table 5. The equivalent fuel consumption (EFC) was obtained from balancing the supercapacitor *SOC*. The equivalent fuel saving ratio (EFSR) is the comparison of EFC, reflecting the energy consumption comparison. The HEB equipped with the ASPF strategy can achieve 23.2% EFSR compared with the

HMB. However, it can only achieve 15.4% and 19.8% EFSR with the PF1 and PF2 strategy, respectively. The ASPF strategy can improve EFSR by 7.8% and 3.4% with respect to the PF1 and PF2 strategy, which indicates that the proposed strategy is more effective.
