Dual planetary-row hybrid systems are widely used in production models of major automotive brands for their superior power and fuel economy. However, only a limited number of configurations have been commercialized, leaving a vast design space unexplored. This paper proposes a four-stage methodology for designing and screening dual planetary-row multimode hybrid powertrain configurations, based on a chemical molecular topology model. First, molecular modeling of the powertrain is performed. Secondly, the topological indexes is introduced for isomorphism detection of the planetary rows, and the assignment rules of the power sources to the nodes of the planetary rows are defined. Then, clutches are assigned to realize a specific base model. Finally, the dynamics and fuel economy of the new configuration are simulated. The process incorporates appropriate constraints and screening conditions to eliminate invalid designs efficiently. Simulation results demonstrate that the proposed powertrain achieves smooth mode switching, along with excellent fuel economy and dynamic performance.
SaitejaPAshokB.Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles. Renew Sustain Energy Rev2022; 157: 112038.
2.
LüXQuYWangY, et al. A comprehensive review on hybrid power system for PEMFC–HEV: issues and strategies. Energy Convers Manag2018; 171: 1273–1291.
3.
ZhuangWLiSZhangX, et al. A survey of powertrain configuration studies on hybrid electric vehicles. Appl Energy2020; 262: 114553.
4.
YangYLiPPeiH, et al. Design of all-wheel-drive power-split hybrid configuration schemes based on hierarchical topology graph theory. Energy2022; 242: 122944.
5.
SabriMFMDanapalasingamKARahmatMF. A review on hybrid electric vehicles architecture and energy management strategies. Renew Sustain Energy Rev2016; 53: 1433–1442.
6.
HuJZuGJiaM, et al. Parameter matching and optimal energy management for a novel dual-motor multi-modes powertrain system. Mech Syst Signal Process2019; 116: 113–128.
7.
ZhuangWZhangXZhaoD, et al. Optimal design of three-planetary-gear power-split hybrid powertrains. Int J Automot Technol2016; 17(2): 299–309.
8.
ZhouXQinDYaoM, et al. Representation, generation, and optimization methodology of hybrid electric vehicle powertrain architectures. J Clean Prod2020; 256: 120711.
9.
SunWLiRKongJ, et al. A new method for isomorphism identification of planetary gear trains. Mech Sci2021; 12(1): 193–202.
10.
Prasad Raju PathapatiVVNRRaoAC. A new technique based on loops to investigate displacement isomorphism in planetary gear trains. J Mech Des2002; 124(4): 662–675.
11.
ChenSShanqiGHuM.General mathematical characterization and configuration optimization design method for a multi-mode hybrid power system. Energy2025; 331: 137013.
12.
HuJXueSXinY, et al. Configuration design and performance analysis of a three-power source power transmission system based on lever method. Int J Energy Res2024; 2024(1): 5063992.
13.
FanY.Research on transmission performance of a seven-gear three-degree-of-freedom planetary gear automatic transmission based on graph theory and matrix equation. J Phys Conf Ser2020; 1601(6): 062031.
14.
LiuJMPengHE.A systematic design approach for two planetary gear split hybrid vehicles. Veh Syst Dyn2010; 48(11): 1395–1412.
15.
ZhangXEben LiSPengH, et al. Efficient exhaustive search of power-split hybrid powertrains with multiple planetary gears and clutches. J Dyn Syst Meas Control2015; 137(12): 121006.
16.
WangWSongRGuoM, et al. Analysis on compound-split configuration of power-split hybrid electric vehicle. Mech Mach Theory2014; 78: 272–288.
17.
KimHKumD.Comprehensive design methodology of input- and output-split hybrid electric vehicles: in search of optimal configuration. IEEE/ASME Trans Mechatron2016; 21(6): 2912–2923.
18.
ZhuangWZhangXDingY, et al. Comparison of multi-mode hybrid powertrains with multiple planetary gears. Appl Energy2016; 178: 624–632.
19.
ZhuangWZhangXPengH, et al. Rapid configuration design of multiple-planetary-gear power-split hybrid powertrain via mode combination. IEEE/ASME Trans Mechatron2016; 21(6): 2924–2934.
20.
PeiHHuXYangY, et al. Designing multi-mode power split hybrid electric vehicles using the hierarchical topological graph theory. IEEE Trans Veh Technol2020; 69(7): 7159–7171.
21.
HoangNTYanHS.On the innovation design for two-motor transmissions with eight-link mechanisms in the electric vehicles. Appl Sci2019; 9(1): 140.
22.
PeiHHuXYangY, et al. Configuration optimization for improving fuel efficiency of power split hybrid powertrains with a single planetary gear. Appl Energy2018; 214: 103–116.
23.
DengTTangPSuZ, et al. Systematic design and optimization method of multimode hybrid electric vehicles based on equivalent tree graph. IEEE Trans Power Electron2020; 35(12): 13465–13474.
24.
DengTZhouXZhaoK.A novel design methodology for fixed-shaft hybrid powertrain with a single-motor. Proc Inst Mech Eng D J Automob Eng2024; 238(7): 1774–1791.
25.
DengTGanZXuH, et al. Configuration design and screening of multi-mode double-planetary-gears hybrid powertrains. J Mech Des2022; 144(7): 073301.
26.
ZhangXLiC-TKumD, et al. Prius+ and volt−: configuration analysis of power-split hybrid vehicles with a single planetary gear. IEEE Trans Veh Technol2012; 61(8): 3544–3552.
27.
ZhangYDiaoLJinZ, et al. Topologies, configuration scheme optimization and energy management strategies of vehicular hybrid power systems: an overview. IEEE Trans Transp Electrif2024; 11(2): 6453–6471.
28.
PengZ-XHuJ-BXieT-L, et al. Design of multiple operating degrees-of-freedom planetary gear trains with variable structure. J Mech Des2015; 137(9): 093301.
29.
ZhangXPengHSunJ, et al. Automated Modeling and Mode Screening for Exhaustive Search of Double-Planetary-Gear Power Split Hybrid Powertrains. American Society of Mechanical Engineers, 2014. DOI:10.1115/DSCC2014-6028.
DengTXuHTangP, et al. A novel algorithm for the isomorphism detection of various kinematic chains using topological index. Mech Mach Theory2020; 146: 103740.
KimNRousseauARaskE.Vehicle-level control analysis of 2010 Toyota Prius based on test data. Proc Inst Mech Eng D J Automob Eng2012; 226(11): 1483–1494.
34.
HuYLiWXuK, et al. Energy management strategy for a hybrid electric vehicle based on deep reinforcement learning. Appl Sci2018; 8(2): 187.
35.
LiDXuPGuJ, et al. A review of reliability research in regional integrated energy system: indicator, modeling, and assessment methods. Buildings2024; 14(11): 3428.
36.
YangYMiJHuX, et al. Graph theory modeling and dynamics analysis on the coupled planetary transmission system of HEV. Automot Eng2015; 37(1): 9–15.
