Study of thermal characteristics, fuel consumption and emissions during cold start using an on-board measuring method for SI car real world urban driving

2007 ◽  
Author(s):  
Hu Li ◽  
Gordon E Andrews ◽  
Dimitrios Savvidis ◽  
Basil Daham ◽  
Karl Ropkins ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Thermal Characteristics ◽  
Cold Start ◽  
Measuring Method ◽  
Fuel Consumption And Emissions

Study of Thermal Characteristics and Emissions during Cold Start using an on-board Measuring Method for Modern SI Car Real World Urban Driving

2008 ◽  
Vol 1 (1) ◽  
pp. 804-819 ◽  
Author(s):  
Hu Li ◽  
Gordon E Andrews ◽  
Dimitrios Savvidis ◽  
Basil Daham ◽  
Karl Ropkins ◽  
...  
Keyword(s):  
Real World ◽  
Thermal Characteristics ◽  
Cold Start ◽  
Measuring Method

scholarly journals Real World Fuel Consumption and Emissions From LDVs and HDVs

2019 ◽  
Vol 5 ◽  
Author(s):  
Konstantin Weller ◽  
Silke Lipp ◽  
Martin Röck ◽  
Claus Matzer ◽  
Andreas Bittermann ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Real World ◽  
Fuel Consumption And Emissions

Comparative study of different types of PHEV optimal control strategies in real-world conditions

2017 ◽  
Vol 232 (12) ◽  
pp. 1597-1610 ◽  
Author(s):  
Morteza Montazeri-Gh ◽  
Zeinab Pourbafarani ◽  
Mehdi Mahmoodi-k
Keyword(s):  
Optimal Control ◽  
Fuel Consumption ◽  
Energy Management ◽  
Real World ◽  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Minimum Principle ◽  
Driving Cycles ◽  
Different Types ◽  
Fuel Consumption And Emissions

With increasingly serious global environmental issues and energy shortages, energy conservation in transportation has become a significant, fundamental objective. The objective of the current research is to investigate the impacts of different types of optimal control strategies on the plug-in hybrid electric vehicle (PHEV) performance in real-world conditions. The optimal control strategies according to Pontryagin’s minimum principle (PMP) and optimized rule-based approaches are developed for the optimal pattern of a PHEV energy management system to reduce fuel consumption and emissions simultaneously, without sacrificing the vehicle performance. For this purpose, first, using test data for engine and battery, an experimental map-based model of the parallel PHEV is developed. Then, the powertrain components are sized by using a genetic algorithm (GA), over the real-world driving cycles. Subsequently, GA-fuzzy and PMP controllers are developed for energy management of the PHEV. Simulation results show the significant effectiveness of the proposed optimal control approaches on the fuel consumption and emissions reduction in various driving cycles. The convergence speed and global searching ability of PMP are significantly better than GA-fuzzy for the design of control strategy parameters. The sensitivity of battery initial state of charge, driving cycle, and road grade are analyzed on vehicle emissions and fuel consumption. The findings reveal that PMP could be adapted to different conditions by tuning co-state in a short time. This advantage makes it more adaptable to variation of real-world conditions. On the other hand, a fuzzy controller needs less computational effort and so is more appropriate for a certain condition.

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