Parameter Matching and Optimization of a Series Hybrid Electric Vehicle Powertrain System

Parameter Matching ◽

Hybrid Electric ◽

Increasing Demand ◽

Hybrid Configuration

The gradual decline of oil reserves and the increasing demand for energy have resulted in automotive manufacturers developing new environmentally friendly vehicles such as electric and hybrid vehicles. Selection of the correct hybrid configuration for a given driving condition is very important since it affects the performance of the vehicle and its fuel economy. This paper focuses on a detailed parametric analysis of a Series Hybrid Electric vehicle (SHEV). The objective of this paper was to develop a SHEV powertrain by initial parameter matching and component sizing, followed by its optimization for given design constraints. This involved study and calculation of components power specifications based on vehicle dynamics. Initial parameterization was followed by optimization to meet the design objective. The simulation of the optimized SHEV was done in the software ADVISOR for an Indian driving cycle (IDC). Based on the simulation results, an optimum range of the powertrain components was established.

Research on Simulation Algorithm of Series Hybrid Electric Vehicle Energy and Intelligent Control

International Journal of Advanced Pervasive and Ubiquitous Computing ◽

10.4018/ijapuc.2017100103 ◽

2017 ◽

Vol 9 (4) ◽

pp. 33-77

Author(s):

Tao Gao

Keyword(s):

Electric Vehicle ◽

Hybrid Electric Vehicle ◽

Practical Significance ◽

Pollutant Emission ◽

Parameter Matching ◽

Hybrid Electric ◽

Future Direction ◽

Long Endurance ◽

Simulation Task

Hybrid electric vehicle (HEV) is a kind of new cars with low fuel consumption and low emissions, which combines the advantages of traditional vehicle's long endurance and no-pollution of pure electric vehicles. It represents the future direction of development of vehicle for a period of time. Therefore, the research of HEV technology has important practical significance to the development of China's automobile. This paper takes Shijiazhuang bus as the research object, makes parameter matching according to the parameters of the vehicle, builds the vehicle model using Cruise software, set the simulation task, and studies the control strategy to reduce automobile fuel and pollutant emission targets. The research of this paper has certain directive significance to the modeling and energy optimization of hybrid electric vehicle.

Design of Vehicle Cooling System Architecture for a Heavy Duty Series-Hybrid Electric Vehicle Using Numerical System Simulations

Journal of Engineering for Gas Turbines and Power ◽

10.1115/1.4000587 ◽

2010 ◽

Vol 132 (9) ◽

Cited By ~ 8

Author(s):

Sungjin Park ◽

Dohoy Jung

Keyword(s):

Power Consumption ◽

Electric Vehicle ◽

System Architecture ◽

Hybrid Electric Vehicle ◽

Cooling System ◽

System Simulation ◽

Heavy Duty ◽

Powertrain System ◽

In this study, numerical simulations of the vehicle cooling system and the vehicle powertrain system of a virtual heavy duty tracked series hybrid electric vehicle (SHEV) is developed to investigate the thermal responses and power consumptions of the cooling system. The output data from the powertrain system simulation are fed into the cooling system simulation to provide the operating conditions of powertrain components. Three different cooling system architectures constructed with different concepts are modeled and the factors that affect the performance and power consumption of each cooling system are identified and compared with each other. The results show that the cooling system architecture of the SHEV should be developed considering various cooling requirements of powertrain components, power management strategy, performance, parasitic power consumption, and the effect of driving conditions. It is also demonstrated that a numerical model of the SHEV cooling system is an efficient tool to assess design concepts and architectures of the system during the early stage of system development.

A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Energies ◽

10.3390/en14113147 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3147

Author(s):

Kiyoung Kim ◽

Namdoo Kim ◽

Jongryeol Jeong ◽

Sunghwan Min ◽

Horim Yang ◽

...

Keyword(s):

Energy Efficiency ◽

Electric Vehicle ◽

Optimization Algorithm ◽

Hybrid Electric Vehicle ◽

New Technologies ◽

New Technology ◽

Dynamic Performance ◽

Minimum Principle ◽

Component Sizing ◽

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.

Multi-objective energy management for Atkinson cycle engine and series hybrid electric vehicle based on evolutionary NSGA-II algorithm using digital twins

Energy Conversion and Management ◽

10.1016/j.enconman.2020.113788 ◽

2021 ◽

Vol 230 ◽

pp. 113788 ◽

Cited By ~ 1

Author(s):

Yangyang Li ◽

Shuqian Wang ◽

Xiongbo Duan ◽

Shujing Liu ◽

Jingping Liu ◽

...

Keyword(s):

Electric Vehicle ◽

Energy Management ◽

Hybrid Electric Vehicle ◽

Nsga Ii ◽

Multi Objective ◽

Atkinson Cycle ◽

Digital Twins ◽

Match and Optimization of Series Hybrid Bus Powertrain Parameters

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.121-126.2710 ◽

2011 ◽

Vol 121-126 ◽

pp. 2710-2714

Author(s):

Ling Cai ◽

Xin Zhang

Keyword(s):

Electric Vehicle ◽

Fuel Economy ◽

Hybrid Electric Vehicle ◽

Simulation Platform ◽

Optimal Method ◽

Orthogonal Method ◽

Hybrid Bus ◽

Promising Solution ◽

With the requirements for reducing emissions and improving fuel economy, it has been recognized that the electric, hybrid electric powered drive train technologies are the most promising solution to the problem of land transportation in the future. In this paper, the parameters of series hybrid electric vehicle (SHEV), including engine-motor, battery and transmission, are calculated and matched. Advisor software is chosen as the simulation platform, and the major four parameters are optimized in orthogonal method. The results show that the optimal method and the parameters can improve the fuel economy greatly.