Improvement of PHEV Equivalent Fuel Economy and Battery Life by Applying Traffic-Based SOC Management

2021 ◽  
pp. 1-1
Author(s):  
Zeinab Pourbafarani ◽  
Morteza Montazeri-Gh ◽  
Masoud Khasheinejad
Keyword(s):  
Fuel Economy ◽  
Battery Life ◽  
Equivalent Fuel

Fuel Economy and Emission Performance of Fuel Cell-Based Diesel HEVs

2008 ◽  
Vol 5 (1) ◽  
Author(s):  
Daniel Crunkleton ◽  
Robert Strattan
Keyword(s):  
Fuel Cell ◽  
Fuel Economy ◽  
Energy Use ◽  
Hybrid Powertrain ◽  
Emission Analysis ◽  
Vehicle Architecture ◽  
Equivalent Fuel ◽  
And Performance ◽  
Hybrid Electric Powertrain ◽  
Powertrain Configuration

The fuel economy and emission advantages of diesel-electric hybrid powertrain modifications and an auxiliary fuel cell subsystem over those of a conventional midsize crossover SUV are discussed. The vehicle architecture is representative of one selected for the multiyear ChallengeX intercollegiate student design contest. To analyze the fuel economy, a simple “top-level” approach is used to estimate the fuel economy characteristics and performance potential to illustrate the advantages of the hybrid-electric powertrain configuration and the auxiliary fuel cells. Chained energy efficiency assumptions for the powertrain components lead to gasoline equivalent fuel mileage estimates. In the emission analysis, the greenhouse gases, regulated emissions, and energy use in transportation model is used to track the environmental impact of the powertrain on a well-to-wheels basis.

scholarly journals Minimum Energy Management Strategy of Equivalent Fuel Consumption of Hybrid Electric Vehicle Based on Improved Global Optimization Equivalent Factor

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2076 ◽  
Author(s):  
Xixue Liu ◽  
Datong Qin ◽  
Shaoqian Wang
Keyword(s):  
Energy Management ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
High Efficiency ◽  
Energy Management Strategy ◽  
Target Value ◽  
Equivalent Fuel ◽  
Equivalent Factor ◽  
Equivalent Fuel Consumption ◽  
Engine Operating Point

A parallel hybrid electric vehicle (PHEV) is used to investigate the fuel economy effect of the equivalent fuel consumption minimization strategy (ECMS) with the equivalent factor as the core, where the equivalent factor is the conversion coefficient between fuel thermal energy and electric energy. In the conventional ECMS strategy, the battery cannot continue to discharge when the state of charge (SOC) is lower than the target value. At this time, the motor mainly works in the battery charging mode, making it difficult to adjust the engine operating point to the high-efficiency zone during the acceleration process. To address this problem, a relationship model of the battery SOC, vehicle acceleration a, and equivalent factor S was established. When the battery SOC is lower than the target value and the vehicle demand torque is high, which makes the engine operating point deviate from the high-efficiency zone, the time that the motor spends in the power generation mode during the driving process is reduced. This enables the motor to drive the vehicle at the appropriate time to reduce the engine output torque, and helps the engine operate in the high-efficiency zone. The correction function under US06 condition was optimized by genetic algorithm (GA). The best equivalent factor MAP was obtained with acceleration a and battery SOC as independent variables, and the improved global optimal equivalent factor of ECMS was established and simulated offline. Simulation results show that compared with conventional ECMS, the battery still has positive power output even when the SOC is less than the target value. The SOC is close to the target value after the cycle condition, and fuel economy improved by 1.88%; compared with the rule-based energy management control strategies, fuel economy improved by 10.17%. These results indicate the effectiveness of the proposed energy management strategy.

Ambient Temperature Effects on Battery Electric Vehicle

2020 ◽  
Author(s):  
Yiqun Liu ◽  
Y. Gene Liao ◽  
Ming-Chia Lai
Keyword(s):  
Ambient Temperature ◽  
Electric Vehicle ◽  
Fuel Economy ◽  
Battery Pack ◽  
Battery Electric Vehicle ◽  
Vehicle Performance ◽  
Production Type ◽  
Battery Capacity ◽  
Equivalent Fuel ◽  
Driving Range

Abstract The driving range of an electric vehicle depends on the vehicle weight, road load conditions, battery capacity, and battery performance. The battery rated capacity and its characteristics could be heavily affected by the ambient temperature. This paper investigates the effects of ambient temperature on the electric vehicle driving range, equivalent fuel economy, and performance. A production-type battery electric vehicle is modeled and simulated in the AVL-Cruise platform using semi-empirical data. The modeled vehicle battery pack consists of 20Ah Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) cells. The battery cell characteristics are experimentally measured to build the battery pack model. The simulated driving range and equivalent fuel economy are correlated with the published information as vehicle model validation. Series of simulations on driving cycles (UDDS, HWFET, US06, and WLTP) with across a broad range of ambient temperatures are conducted to investigate the quantified effects of ambient temperature on driving range, equivalent fuel economy, and vehicle performance. Simulation results show that driving range and fuel economy are much reduced to 70% at low ambient temperature. Driving range and fuel economy are almost not affected by high ambient temperature, such as 50 C, since this model does not include accessory load of thermal management. The vehicle performance is almost not affected by the ambient temperature.

Optimal Equivalent Consumption Minimization Strategy for Plug-In Hybrid Electric Vehicle with Improved Genetic Algorithm

2020 ◽  
Vol 9 (2) ◽  
pp. 143-154
Author(s):  
Changyin Wei ◽  
◽  
Yong Chen ◽  
Xiuxiu Sun ◽  
Yue Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Energy Management ◽  
Fuel Economy ◽  
Battery Life ◽  
Improved Genetic Algorithm ◽  
Life Index ◽  
Battery Capacity ◽  
Equivalent Factor ◽  
Equivalent Consumption Minimization Strategy

The equivalent consumption minimization strategy (ECMS) is a promising energy management approach to low-fuel economy with the outstanding features of high efficiency. In this article, an optimal ECMS by Improved Genetic Algorithm (IGA) is proposed. To this end, we improved the genetic algorithm (GA) from the coding method, initialization mode, and cross and mutation process. And based on the comprehensive energy consumption and Pontryagin’s minimum principle, the equivalent factor was derived. The IGA was used to optimize the equivalent factor. To evaluate the performance of the proposed energy management strategy (EMS), the average efficiency of the engine and the motor was analyzed in an urban area, high-speed area, and the whole area. The comprehensive fuel consumption was used as the energy consumption index, and the battery capacity loss under the transient conditions was amplified to 10 years as the evaluation battery life index. The simulation results show that under the New European Driving Cycle (NEDC), the proposed strategy improves the fuel economy and battery life index by 14.64% and 36.76%, respectively, compared with the rule-based EMS.

scholarly journals Support vector machine–based driving cycle recognition for dynamic equivalent fuel consumption minimization strategy with hybrid electric vehicle

2018 ◽  
Vol 10 (11) ◽  
pp. 168781401881102
Author(s):  
QIN Shi ◽  
Duoyang Qiu ◽  
Lin He ◽  
Bing Wu ◽  
Yiming Li
Keyword(s):  
Support Vector Machine ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Driving Cycle ◽  
Support Vector ◽  
Equivalent Fuel ◽  
Hybrid Electric ◽  
Equivalent Fuel Consumption

For a great influence on the fuel economy and exhaust, driving cycle recognition is becoming more and more widely used in hybrid electric vehicles. The purpose of this study is to develop a method to identify the type of driving cycle in real time with better accuracy and apply the driving cycle recognition to minimize the fuel consumption with dynamic equivalent fuel consumption minimization strategy. The support vector machine optimized by the particle swarm algorithm is created for building driving cycle recognition model. Furthermore,the influence of the two parameters of window width and window moving velocity on the accuracy is also analyzed in online application. A case study of driving cycle in a medium-sized city is introduced based on collecting four typical driving cycle data in real vehicle test. A series of characteristic parameters are defined and principal component analysis is used for data processing. Finally, the driving cycle recognition model is used for equivalent fuel consumption minimization strategy with a parallel hybrid electric vehicle. Simulation results show that the fuel economy can improve by 9.914% based on optimized support vector machine, and the fluctuations of battery state of charge are more stable so that system efficiency and batter life are substantially improved.

scholarly journals Analysis of Fuel Economy and Battery Life depending on the Types of HEV using Dynamic Programming

2013 ◽  
Vol 6 (2) ◽  
pp. 320-324
Author(s):  
Jongryeol Jeong ◽  
Jongwoo Choi ◽  
Howon Seo ◽  
Yeong-il Park ◽  
Suk Cha
Keyword(s):  
Dynamic Programming ◽  
Fuel Economy ◽  
Battery Life
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