A design methodology for hybrid electric vehicle powertrain configurations with planetary gear sets

2020 ◽  
pp. 1-16
Author(s):  
Xingyue Jiang ◽  
Jianjun Hu ◽  
Hang Peng ◽  
Zhipeng Chen

Abstract Increasingly strict emission and fuel economy standards stimulates the researches on hybrid electric vehicle techniques in automobile industry and one of the most important techniques is the design of powertrain configurations. In this paper, a theoretical design methodology for hybrid electric vehicle powertrain configurations is proposed to find the configurations with excellent performance in a large pool of configurations. There are two main parts in a powertrain configuration, power/coupling devices (engine, electric machine, wheel and planetary gear set) and mechanical connections between these devices. Different connections will lead to the configurations having different performance. This paper divides all connections in configurations into three categories and a novel matrix representation method is developed to express these kinds of connections so as to reflect system dynamics and physical structure of configurations. With the support of the matrix representation method, configuration selections from large pools can automatically be completed by computer and manually calculation and comparison can be avoided, which saves much energy and time. Finally, the proposed method is vigorously verified by simulations.

Author(s):  
Pier Giuseppe Anselma ◽  
Yi Huo ◽  
Joel Roeleveld ◽  
Ali Emadi ◽  
Giovanni Belingardi

This work aims at presenting a design methodology capable of modeling, generating, and testing a large number of multimode power split hybrid electric vehicle transmission designs in a relatively short period of time. Design parameters include the planetary gear ratios, the final drive ratio, the configuration of hookups to link the hybrid powertrain components to the planetary gear sets and the locations of clutch connections between different nodes of the planetary gear sets. The system modeling approach is first presented, including formulations for each component (the vehicle and road load, the engine, the motor/generators and the battery). A rapid and automated modeling procedure is proposed for hybrid electric vehicle transmissions including multiple planetary gear sets and clutch connections. Two algorithms are subsequently presented that enable fast evaluation of fuel economy and acceleration performance of hybrid electric vehicle transmission designs, namely the enhanced Power-Weighted Efficiency Analysis for Rapid Sizing and the Rapid Efficiency-based Launching Performance Analysis algorithms. The developed design methodology is tested by first modeling and evaluating three hybrid electric vehicle designs from the state-of-art. Later, an investigation for optimal designs that can ameliorate the examined benchmarks is performed. Several millions of design options are rapidly generated and tested using the proposed procedure. The methodology is proved effective by quickly coming up with two sub-optimal designs. Fuel economy and acceleration performance are improved by 5.56% and 40.56%, respectively, compared to the corresponding best benchmarks.


Author(s):  
Alparslan Emrah Bayrak ◽  
Yi Ren ◽  
Panos Y. Papalambros

A hybrid-electric vehicle powertrain architecture consists of single or multiple driving modes, i.e., connection arrangements among engine, motors and vehicle output shaft that determine distribution of power. While most architecture development work to date has focused primarily on passenger cars, interest has been growing in exploring architectures for special-purpose vehicles such as vans or trucks for civilian and military applications, whose weights or payloads can vary significantly during operations. Previous findings show that the optimal architecture can be sensitive to vehicle weight. In this paper we investigate architecture design under a distribution of vehicle weights, using a simulation-based design optimization strategy with nested supervisory optimal control and accounting for powertrain complexity. Results show that an architecture under a single load has significant differences and lower fuel efficiency than an architecture designed to work under a variety of loading scenarios.


2019 ◽  
Vol 52 (5) ◽  
pp. 141-146 ◽  
Author(s):  
Pier Giuseppe Anselma ◽  
Yi Huo ◽  
Joel Roeleveld ◽  
Giovanni Belingardi ◽  
Ali Emadi

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