## 6 Conclusions  
This study considered a novel HEV with dual motors as the research object. Based on the structural characteristics of the powertrain system, the working modes of the combined gears were proposed for a gear shift. Furthermore, this study investigated the control effects of various motor rotary velocity control algorithms with different target rotary velocities. At the same time, this paper also proposes a dynamic coordinated control strategy to achieve better shift quality. The main conclusions are as follows. 1. When the PID algorithm was applied to the motor rotary velocity control system, with an increase in the target rotary velocity, the rise time and peak time of the motor rotary velocity regulation were basically unchanged, while the regulation time and maximum overshoot both gradually increased with an approximately linear growth trend. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Gear Shift Control Strategy** & **Shift Time** & **Maximum Jerk** & **CL2 Slipping Friction Work** \\ \hline Based on PID & 0.42 s & 1.46 m/s\({}^{3}\) & 1017 J \\ Based on PID–bang-bang–fuzzy & 0.27 s & 3.77 m/s\({}^{3}\) & 821.3 J \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of shift evaluation indexes. Figure 23: Simulation results based on PID–bang-bang–fuzzy compound intelligent control algorithm. (**a**) Rotary velocity and pressure of CL2; (**b**) torque of power source and CL2; (**c**) output torque of gearbox output shaft; (**d**) jerk and slipping friction work. 2. When the PID-bang-bang compound algorithm was applied to the motor rotary velocity control system, as the target rotary velocity was increased, the rise time, peak time, and regulation time of the motor rotary velocity regulation gradually increased with an approximately linear growth trend. Meanwhile, the maximum overshoot also gradually increased with a nonlinear increasing trend. 3. When the PID-bang-bang-fuzzy compound intelligent algorithm was applied to a motor rotary velocity control system, with an increase in the target rotary velocity, the rise time, peak time, and regulation time of the motor rotary velocity regulation gradually increased, and it showed an approximately linear growth trend. However, the maximum overshoot gradually decreased, and its decreasing trend presented a nonlinear law. Furthermore, when the target rotary velocity was a constant value (3000 rpm), with an increase in the algorithm threshold, the rise time of the motor rotary velocity regulation remained unchanged. The peak time, regulation time, and maximum overshoot gradually decreased, and the decreasing trend was nonlinear. 4. For the motor rotary velocity regulation control algorithm, different control algorithms have different effects on the rotary velocity regulation effect. Compared with PID and PID-bang-bang, the steady-state response and dynamic response of the motor rotary velocity regulation process are significantly improved by using the PID-bang-bang-fuzzy compound intelligent control algorithm proposed in this paper. 5. In this paper, a coordinated control strategy for shifting gears, based on motor rotary velocity regulation, is designed for the novel hybrid electric vehicle. Compared with the gear shift coordinated control strategy based on the PID control algorithm, the control strategy, based on the PID-bang-bang-fuzzy compound intelligent control algorithm proposed in this paper, reduced the shift time and clutch slipping friction work by 35.7% and 19.2%, respectively. Conceptualization, Q.X. ; methodology, Q.X. and X.Z. ; software, Q.X. and X.Z. ; formal analysis, Q.X. and C.G. ; investigation, C.G. and T.T. ; data curation, Q.X. and X.Z. ; writing--original draft preparation, Q.X. and X.Z. ; writing--review and editing, Q.X., X.Z. and C.G. ; visualization, C.G. ; supervision, X.Z. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Key Research and Development Program of China (Grant No. 2017 YFB0103203). Not applicable.