# Integrating Gear Shifting Preference into Personalized Shift-Scheduling Calibration
## 3 The Proposed Scheme for Preference Integration and Automated Shift-Scheduling Calibration
### Preference Integration and Automated Calibration of Shift Scheduling  
Figure 4 illustrates the shift-scheduling calibration system adopted in this work, which could be automated by the PSO to guide the optimization process. The robot driver (driver model) is employed to retain and reproduce the MT driving preferences via the CMAC neural network and the real-world vehicle test data (VTD). With regard to a particular candidate schedule, the vehicle (model) is manipulated by the robot driver to follow the pre-defined standard driving cycle, i.e., FTP-72 in this paper. The shifting performance is then assessed based on the performance index. This procedure is repeatedly conducted on each candidate schedule or particle, and could eventually find an optimal or near-optimal solution. The automated shift-scheduling optimization proceeds as illustrated in Figure 5. In the searching space, a group of candidate shifting schedules are produced randomly within the overlapped zone of MT shifting points and the space around the base map of specific vehicle type as initial particles. For each candidate schedule, the evaluation of performance index (PI) is implemented by a robot driver after each driving cycle test. In each test, the robot driver (model) is employed to manipulate the vehicle (model) equipped with a set of candidate shifting schedules to track the expected velocity profile. When the shifting performance evaluation of all candidate schedules is done, the new candidate schedules will be generated via PSO according to the position and velocity update of each particle in the group. The aforementioned procedures are repeatedly conducted until the optimal shift schedule is found or a maximum iteration is reached. The proposed method could also be applied in other vehicle types by changing the initial searching space based on specific shift map. Figure 4: Block diagram of automated calibration system. The optimization is conducted via the following steps:  
1. Determining the searching space of the shifting-schedules In consideration of the drivers' shifting preferences, the shifting points of MT drivers are collected for each kind of shifting event. Then, the searching space is obtained by the overlapped zone of MT shifting points and the space around the base map. 2. Initializing the candidate shifting schedules Each particle is a 150-dimension vector, which stands for 150 shifting points of the shift map. The candidate shifting schedules are generated in the aforementioned searching space. 3. Decide the operations of the driver model At current time \(t\), suppose that the real and expected vehicle speeds are \(VS[t]\) and \(VS^{*}[t]\), and the throttle position is \(TP[t]\). However, due to the time delay of the system, the \(TP[t]\) will not impact on the vehicle speed until time \(t+k\). The operation of robot driver model are determined by its input \(VS^{*}[t]\) and \(\Delta VS[t]\), where \[\Delta VS[t]\ =\ VS^{*}[t]\ -\ VS[t]\] (11)  
Considering it is not permitted to step on the gas pedal and brake pedal at the same time, at least one of \(TP\) and \(BP\) must be zero. As a rough estimation, the sum of \(TP\) during shifting events will be further analyzed for fuel consumption. 4. Adjust the intervals of candidate schedules  
Figure 5: Flowchart of automated optimization process. In order to avoid unnecessary and repeated gear-shifts, it is important to maintain proper shift delay between adjacent upshift and downshift curves [7]. The shift delay is set to adjust the intervals of candidate schedules, which is defined according to the base shift map as,  
\[A_{n}=\frac{V_{n}\uparrow-V_{n+1}\downarrow}{V_{n}\uparrow} \tag{12}\]  
where \(V_{n}\uparrow\) is the upshift speed from gear(\(n\)) to gear(\(n+1\)) at given TP position and \(V_{n+1}\downarrow\) is the downshift speed from gear(\(n+1\)) to gear(\(n\)) at given TP position. \(A_{n}\) is computed according to the base shift map.