In order to improve the shift quality of vehicles under different operating conditions (such as road resistance coefficient and throttle opening), this paper proposes an adaptive coordinated control strategy. This strategy utilizes a Forgetting Factor Recursive Least Squares (FFRLS) to achieve online identification of the road resistance coefficient. Based on the changes in throttle pedal opening and road resistance coefficient during the vehicle’s shifting process, the strategy adaptively adjusts the coordinated control parameter (fuel cut-off time) to achieve optimal control of vehicle shifting under different operating conditions. To evaluate the shift quality, shift jerk, friction work, torque peak, and shift time are used as performance indicators. Based on a constructed simulation model of the powertrain system, the influence of different operating conditions on the performance indicators is analyzed, and the effect of coordinated control parameters on improving shift quality under different operating conditions is compared. Corresponding fuzzy rules are then established to achieve adaptive adjustment of the coordinated control parameters through fuzzy control, ensuring effective improvement of shift quality for vehicles under different operating conditions.
DongPLiuYTenbergeP, et al. Design and analysis of a novel multi-speed automatic transmission with four degrees-of-freedom. Mech Mach Theory2017; 108: 83–96.
2.
RanogajecVDeurJIvanovićV, et al. Multi-objective parameter optimization of control profiles for automatic transmission double-transition shifts. Control Eng Pract2019; 93: 1–13.
3.
SanadaKGaoBKadoN, et al. Design of a robust controller for shift control of an automatic transmission. Proc IMechE, Part D: J Automobile Engineering2012; 226(12): 1577–1584.
4.
RanogajecVDeurJCoricM. Bond graph analysis of automatic transmission shifts including potential of extra clutch control. SAE Int J Engines2016; 9(3): 1929–1945.
5.
ChengYDongPYangS, et al. Virtual clutch controller for clutch-to-clutch shifts in planetary-type automatic transmission. Math Probl Eng2015; 2015(1): 1–16.
6.
ZhangHZhaoXSunJ. Optimal clutch pressure control in shifting process of automatic transmission for heavy-duty mining trucks. Math Probl Eng2020; 2020(1): 1–9.
7.
MengFTaoGZhangT, et al. Optimal shifting control strategy in inertia phase of an automatic transmission for automotive applications. Mech Syst Signal Process2015; 60-61: 742–752.
8.
ZhangYHariaHHippalgaonkarR, et al. Automatic transmission shift control for canceling inertia torque. SAE technical papers, 2018.
9.
CvokIRanogajecVDeurJ, et al. Analysis of improving automatic transmission upshift performance by using off-going clutch during inertia phase. J Dyn Syst Meas Control2022; 144(2): 1–13.
10.
HongSSonHLeeS, et al. Shift control of a dry-type two-speed dual-clutch transmission for an electric vehicle. Proc IMechE, Part D: J Automobile Engineering2016; 230(3): 308–321.
11.
CvokISoldoJDeurJ, et al. Model predictive control for automatic transmission upshift inertia phase. IEEE Trans Control Syst Technol2023; 31(6): 2335–2349.
12.
ČorićMRanogajecVDeurJ, et al. Optimization of shift control trajectories for step gear automatic transmissions. J Dyn Syst Meas Control2017; 139(6): 1–40.
13.
RanogajecVIvanovićVDeurJ, et al. Optimization-based assessment of automatic transmission double-transition shift controls. Control Eng Pract2018; 76: 155–166.
14.
ShangXZhangFWangJ, et al. Multi-objective parameter optimization strategy based on engine coordinated control for improving shifting quality. Adv Mech Eng2023; 15(12): 1–12.
15.
OuyangTLiSHuangG, et al. Controller design for uncertain dynamics of smooth shift of heavy-duty automatic transmission. Appl Math Model2020; 85: 157–173.
16.
OhJJEoJSChoiSB. Torque observer-based control of self-energizing clutch actuator for dual clutch transmission. IEEE Trans Control Syst Technol2017; 25(5): 1856–1864.
17.
DingZChenLMiaoD. Decoupling internal model control for the robust engagement of clutches. Mechatronics2021; 73: 1–12.
18.
WangEMengF. Down shift control with power of planetary-type automatic transmission for a heavy-duty vehicle. Mech Syst Signal Process2021; 159: 1–14.
19.
CvokIDeurJIvanovicV, et al. An LQR approach of automatic transmission upshift control including use of off-going clutch within inertia phase. SAE Int J Adv Curr Prac Mobil2020; 2(4): 2081–2089.
20.
SoldoJCvokIDeurJ, et al. Automatic transmission upshift control using a linearized reduced-order model-based lqr approach. SAE Tech Pap Ser2021; 1(0697): 2291–2300.
21.
XiaGChenJTangX, et al. Shift quality optimization control of power shift transmission based on particle swarm optimization–genetic algorithm. Proc IMechE, Part D: J Automobile Engineering2022; 236(5): 872–892.
22.
WangJLiRHuangY, et al. Coordinated gear shift process control based on engine speed. In: International conference on vehicular control and intelligence, Tianjin, China, 29–31 October 2021. New York: IEEE.
23.
FuYLiuYCuiL, et al. Dynamic analysis and control strategy of wet clutches during torque phase of gear shift. J Mech Sci Technol2016; 30(4): 1479–1496.
24.
ZhangHZhaoXYangJ, et al. Optimizing automatic transmission double-transition shift process based on multi-objective genetic algorithm. Appl Sci2020; 10(21): 7794–7814.
25.
ZhaoXLiZ. Data-driven predictive control applied to gear shifting for heavy-duty vehicles. Energies2018; 11(8): 2139–2214.
26.
WuJYanHLiuS, et al. Bond graph-based approach to modeling variable-speed gearboxes with multi-type clutches. Appl Sci2022; 12(12): 6181–6229.
27.
RanogajecVDeurJ. Bond graph analysis and optimal control of the hybrid dual clutch transmission shift process. Proc IMechE, Part K: J Multi-body Dynamics2017; 231(3): 480–492.
28.
AwadallahMTawadrosPWalkerP, et al. Dynamic modelling and simulation of a manual transmission based mild hybrid vehicle. Mech Mach Theory2017; 112: 218–239.
29.
ChoiMOhJJChoiSB. Linearized recursive least squares methods for real-time identification of tire–road friction coefficient. IEEE Trans Vehicular Technol2013; 62(7): 2906–2918.
30.
ChenZCuiWCuiX, et al. A new method of insulation detection on electric vehicles based on a variable forgetting factor recursive least squares algorithm. IEEE Access2021; 9(1): 73590–73607.
31.
FengBYinGRenY, et al. A joint vehicle mass and road slope estimation of distributed drive electric vehicles considering road environment factors. In: International conference on intelligent transportation systems, 8–12 October 2022. New York: IEEE.
32.
FengJQinDLiuY, et al. Pseudo-spectral optimization and model predictive control of vehicle shift process with dual clutch transmission. Proc IMechE, Part C: J Mechanical Engineering Science2023; 237(16): 3789–3806.
33.
LiBSunDHuM, et al. Coordinated control of gear shifting process with multiple clutches for power-shift transmission. Mech Mach Theory2019; 140: 274–291.
34.
LiuYZhangJHuangQ, et al. Optimal clutch torque prediction for shifting process of dual clutch transmission based on support vector regression. Int J Autom Technol2022; 23(4): 1073–1084.
35.
HaviezLFouvrySYantioG. Optimal control of the gear shifting process for shift smoothness in dual-clutch transmissions. Mech Syst Signal Process2018; 103: 23–38.
