A unified quantitative analysis of fuel economy for hybrid electric vehicles based on energy flow

Hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) are evolving rapidly since the introduction of Toyota Prius into the market in 1997. As the world needs more fuel-efficient vehicles to mitigate climate change, the role of HEVs and PHEVs are becoming ever more important. While fuel economies of HEVs and PHEVs are superior to those of internal combustion engine (ICE) powered vehicles, they are partially powered by batteries and therefore they resemble characteristics of battery electric vehicles (BEVs) such as dependence of fuel economy on ambient temperatures. It is also important to understand how different extent of hybridization (a.k.a., hybridization ratio) affects fuel economy under various driving conditions. In addition, it is of interest to understand how HEVs and PHEVs compare with BEVs at a similar vehicle weight. This study investigated the relationship between vehicle mass and vehicle performance parameters, mainly fuel economy and driving range of PHEVs focused on 2018 and 2019 model years using the test data available from fuel economy website of the US Environmental Protection Agency (EPA). Previous studies relied on modeling to understand mass impact on fuel economy for HEV as there were not enough number of HEVs in the market to draw a trendline at the time. The study also investigated the effect of ambient temperature for HEVs and PHEVs and kinetic energy recovery of the regenerative braking using the vehicle testing data for model year 2013 and 2015 from Idaho National Lab (INL). The current study assesses current state-of-art for PHEVs. It also provides analysis of experimental results for validation of vehicle dynamic and other models for PHEVs and HEVs.

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Model predictive control of hybrid electric vehicles for fuel economy, emission reductions, and inter-vehicle safety in car-following scenarios

Energy ◽

10.1016/j.energy.2020.117101 ◽

2020 ◽

Vol 196 ◽

pp. 117101 ◽

Cited By ~ 1

Author(s):

Xiaosong Hu ◽

Xiaoqian Zhang ◽

Xiaolin Tang ◽

Xianke Lin

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Electric Vehicles ◽

Fuel Economy ◽

Hybrid Electric Vehicles ◽

Vehicle Safety ◽

Emission Reductions ◽

Car Following ◽

Hybrid Electric

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Depleting Mode Control Strategies for Plug-in Hybrid Electric Vehicles

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.130-134.2211 ◽

2011 ◽

Vol 130-134 ◽

pp. 2211-2215

Author(s):

Bing Zhan Zhang ◽

Han Zhao ◽

An Dong Yin

Keyword(s):

Electric Vehicles ◽

Fuel Economy ◽

Control Strategy ◽

Hybrid Electric Vehicles ◽

Control Strategies ◽

Great Influence ◽

Torque Control ◽

Drive Cycle ◽

Vehicle Simulation ◽

Hybrid Electric

Control strategy is the most important issue in the Plug-in Hybrid electric vehicles (PHEV) design, which has two modes: charge depleting mode (CD) and charge sustaining mode (CS). The different control strategies in depleting mode will have a great influence on PHEV dynamic performance and fuel economy. The engine optimal torque control strategy was proposed in the paper. The vehicle simulation model in Powertrain Systems Analysis Toolkit (PSAT) was adopted to evaluate the proposed control strategy. The aggressive highway drive cycle Artemis_hwy and a random drive cycle generated by Markov Process were used. The simulation results indicate the proposed control strategy has great improvement in fuel economy.

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Recommended Practice for Measuring the Exhaust Emissions and Fuel Economy of Hybrid-Electric Vehicles

10.4271/j1711_199903 ◽

1999 ◽

Author(s):

Keyword(s):

Electric Vehicles ◽

Fuel Economy ◽

Hybrid Electric Vehicles ◽

Exhaust Emissions ◽

Hybrid Electric

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Effects of Drivetrain Hybridization on Fuel Economy and Dynamic Performance of Parallel Hybrid Electric Vehicles

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2004.823525 ◽

2004 ◽

Vol 53 (2) ◽

pp. 385-389 ◽

Cited By ~ 157

Author(s):

S.M. Lukic ◽

A. Emadi

Keyword(s):

Electric Vehicles ◽

Fuel Economy ◽

Hybrid Electric Vehicles ◽

Dynamic Performance ◽

Parallel Hybrid ◽

Hybrid Electric

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Model Predictive Control for Connected Hybrid Electric Vehicles

Mathematical Problems in Engineering ◽

10.1155/2015/318025 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 12

Author(s):

Kaijiang Yu ◽

Xiaozhuo Xu ◽

Qing Liang ◽

Zhiguo Hu ◽

Junqi Yang ◽

...

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Electric Vehicles ◽

Fuel Economy ◽

Hybrid Electric Vehicle ◽

Hybrid Electric Vehicles ◽

Control Method ◽

Fuel Efficiency ◽

Computation Method ◽

Hybrid Electric

This paper presents a new model predictive control system for connected hybrid electric vehicles to improve fuel economy. The new features of this study are as follows. First, the battery charge and discharge profile and the driving velocity profile are simultaneously optimized. One is energy management for HEV forPbatt; the other is for the energy consumption minimizing problem of acc control of two vehicles. Second, a system for connected hybrid electric vehicles has been developed considering varying drag coefficients and the road gradients. Third, the fuel model of a typical hybrid electric vehicle is developed using the maps of the engine efficiency characteristics. Fourth, simulations and analysis (under different parameters, i.e., road conditions, vehicle state of charge, etc.) are conducted to verify the effectiveness of the method to achieve higher fuel efficiency. The model predictive control problem is solved using numerical computation method: continuation and generalized minimum residual method. Computer simulation results reveal improvements in fuel economy using the proposed control method.

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