A Fully-Analytical Fuel Consumption Estimation for the Optimal Design of Light- and Heavy-Duty Series Hybrid Electric Powertrains

2017 ◽  
Author(s):  
Jianning Zhao ◽  
Antonio Sciarretta
Keyword(s):  
Optimal Design ◽  
Fuel Consumption ◽  
Heavy Duty ◽  
Hybrid Electric ◽  
Electric Powertrains

scholarly journals Real Drive Well-to-Wheel Energy Analysis of Conventional and Electrified Car Powertrains

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4788
Author(s):  
Fabio Orecchini ◽  
Adriano Santiangeli ◽  
Fabrizio Zuccari
Keyword(s):  
Fuel Consumption ◽  
Co2 Emissions ◽  
Technology Development ◽  
Primary Energy ◽  
Urban Streets ◽  
Long Time ◽  
Hybrid Electric ◽  
Driving Conditions ◽  
Electric Powertrains ◽  
Global Emissions

Reducing fuel consumption and global emissions in the automotive sector has been a main focus of vehicle technology development for long time. The most effective goal to achieve the overall sustainability objectives is to reduce the need for non-renewable and fossil resources. Five vehicles, two conventional ICE, two hybrid-electric, and one pure electric powertrain, are considered. Non-renewable primary energy consumption and CO2 emissions are calculated for each powertrain considered. All data—including calculated values—are based on the experimental measure of fuel consumption taken in real driving conditions. The data were recorded in an experimental campaign in Rome, Italy on urban, extra-urban streets, and highway on a total of 5400 km and 197 h of road acquisitions. The analysis shows significant reductions in non-renewable fossil fuel consumption and CO2 emissions of hybrid-electric powertrains compared to conventional ones (petrol and diesel engines). Furthermore, a supplementary and very interesting comparison analysis was made between the values of energy consumptions measured during the tests in real driving conditions and the values deriving from the NEDC and WLTP homologation cycles.

Dynamic Modeling of Heavy-Duty Hybrid Electric Vehicles

2007 ◽  
Author(s):  
Lorenzo Serrao ◽  
Christopher J. Hubert ◽  
Giorgio Rizzoni
Keyword(s):  
Dynamic Performance ◽  
Management Strategies ◽  
Heavy Duty ◽  
Virtual Test ◽  
Heavy Duty Vehicle ◽  
Engine Cylinder ◽  
Hybrid Electric ◽  
Hybrid Electric Powertrain ◽  
Dynamics Models ◽  
Electric Powertrains

The paper presents a dynamic model of a hybrid electric powertrain for a heavy-duty vehicle. The model involves all powertrain components and considers purely longitudinal vehicle dynamics; time constants of 0.05 – 5 seconds are taken into account, thus neglecting high frequency phenomena (NVH, engine cylinder-to-cylinder motion). Integration with handling dynamics models, characterized by the same frequency range, is possible but not discussed here. The simulator is an accurate virtual test bench for energy management strategies applied to hybrid electric powertrains, capable of predicting both fuel consumption and dynamic performance. The accuracy in both metrics is demonstrated by comparison with experimental data collected on a conventional heavy-duty refuse truck and a prototype of a series hybrid electric version of the same vehicle.

Stirling system optimization for series hybrid electric vehicles

2021 ◽  
pp. 095440702110180
Author(s):  
Charbel R Ghanem ◽  
Elio N Gereige ◽  
Wissam S Bou Nader ◽  
Charbel J Mansour
Keyword(s):  
Fuel Consumption ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Optimization Technique ◽  
System Optimization ◽  
Energy Management Strategy ◽  
Fuel Savings ◽  
Auxiliary Power ◽  
Hybrid Electric ◽  
External Combustion

There have been many studies conducted to replace the conventional internal combustion engine (ICE) with a more efficient engine, due to increasing regulations over vehicles’ emissions. Throughout the years, several external combustion engines were considered as alternatives to these traditional ICEs for their intrinsic benefits, among which are Stirling machines. These were formerly utilized in conventional powertrains; however, they were not implemented in hybrid vehicles. The purpose of this study is to investigate the possibility of implementing a Stirling engine in a series hybrid electric vehicle (SHEV) to substitute the ICE. Exergy analysis was conducted on a mathematical model, which was developed based on a real simple Stirling, to pinpoint the room for improvements. Then, based on this analysis, other configurations were retrieved to reduce exergy losses. Consequently, a Stirling-SHEV was modeled, to be integrated as auxiliary power unit (APU). Hereafter, through an exergo-technological detailed selection, the best configuration was found to be the Regenerative Reheat two stages serial Stirling (RRe-n2-S), offering the best efficiency and power combination. Then, this configuration was compared with the Regenerative Stirling (R-S) and the ICE in terms of fuel consumption, in the developed SHEV on the WLTC. This was performed using an Energy Management Strategy (EMS) consisting of a bi-level optimization technique, combining the Non-dominated Sorting Genetic Algorithm (NSGA) with the Dynamic Programming (DP). This arrangement is used to diminish the fuel consumption, while considering the reduction of the APU’s ON/OFF switching times, avoiding technical issues. Results prioritized the RRe-n2-S presenting 12.1% fuel savings compared to the ICE and 14.1% savings compared to the R-S.

Hierarchical energy management strategy considering switching schedule for a dual-mode hybrid electric vehicle

2021 ◽  
pp. 095440702110297
Author(s):  
Hui Liu ◽  
Rui Liu ◽  
Riming Xu ◽  
Lijin Han ◽  
Shumin Ruan
Keyword(s):  
Fuel Consumption ◽  
Energy Management ◽  
Control Strategy ◽  
Power Distribution ◽  
Hybrid Electric Vehicle ◽  
Hierarchical Control ◽  
Management Problem ◽  
Energy Management Strategy ◽  
Dual Mode ◽  
Hybrid Electric

Energy management strategies are critical for hybrid electric vehicles (HEVs) to improve fuel economy. To solve the dual-mode HEV energy management problem combined with switching schedule and power distribution, a hierarchical control strategy is proposed in this paper. The mode planning controller is twofold. First, the mode schedule is obtained according to the mode switch map and driving condition, then a switch hunting suppression algorithm is proposed to flatten the mode schedule through eliminating unnecessary switch. The proposed algorithm can reduce switch frequency while fuel consumption remains nearly unchanged. The power distribution controller receives the mode schedule and optimizes power distribution between the engine and battery based on the Radau pseudospectral knotting method (RPKM). Simulations are implemented to verify the effectiveness of the proposed hierarchical control strategy. For the mode planning controller, as the flattening threshold value increases, the fuel consumption remains nearly unchanged, however, the switch frequency decreases significantly. For the power distribution controller, the fuel consumption obtained by RPKM is 4.29% higher than that of DP, while the elapsed time is reduced by 92.53%.

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