scholarly journals Driving Cycles Based on Fuel Consumption

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3064 ◽  
Author(s):  
José Huertas ◽  
Michael Giraldo ◽  
Luis Quirama ◽  
Jenny Díaz
Keyword(s):  
Fuel Consumption ◽  
Test Procedure ◽  
Region Of Interest ◽  
Driving Cycle ◽  
Normal Operation ◽  
Characteristic Parameters ◽  
Driving Cycles ◽  
Driving Pattern ◽  
Relative Differences ◽  
Fuel Consumption And Emissions

Type-approval driving cycles currently available, such as the Federal Test Procedure (FTP) and the Worldwide harmonized Light vehicles Test Cycle (WLTC), cannot be used to estimate real fuel consumption nor emissions from vehicles in a region of interest because they do not describe its local driving pattern. We defined a driving cycle (DC) as the time series of speeds that when reproduced by a vehicle, the resulting fuel consumption and emissions are similar to the average fuel consumption and emissions of all vehicles of the same technology driven in that region. We also declared that the driving pattern can be described by a set of characteristic parameters (CPs) such as mean speed, positive kinetic energy and percentage of idling time. Then, we proposed a method to construct those local DC that use fuel consumption as criterion. We hypothesized that by using this criterion, the resulting DC describes, implicitly, the driving pattern in that region. Aiming to demonstrate this hypothesis, we monitored the location, speed, altitude, and fuel consumption of a fleet of 15 vehicles of similar technology, during 8 months of normal operation, in four regions with diverse topography, traveling on roads with diverse level of service. In every region, we considered 1000 instances of samples made of m trips, where m varied from 4 to 40. We found that the CPs of the local driving cycle constructed using the fuel-based method exhibit small relative differences (<15%) with respect to the CPs that describe the driving patterns in that region. This result demonstrates the hypothesis that using the fuel based method the resulting local DC exhibits CPs similar to the CPs that describe the driving pattern of the region under study.

scholarly journals Comparison of Three Methods for Constructing Real Driving Cycles

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 665 ◽  
Author(s):  
José Huertas ◽  
Luis Quirama ◽  
Michael Giraldo ◽  
Jenny Díaz
Keyword(s):  
Fuel Consumption ◽  
Normal Operation ◽  
Mcmc Methods ◽  
Characteristic Parameters ◽  
The Real ◽  
Stochastic Nature ◽  
Driving Patterns ◽  
Driving Cycles ◽  
Relative Differences ◽  
Fuel Consumption And Emissions

This work compares the Micro-trips (MT), Markov chains–Monte Carlo (MCMC) and Fuel-based (FB) methods in their ability of constructing driving cycles (DC) that: (i) describe the real driving patterns of a given region and (ii) reproduce the real fuel consumption and emissions exhibited by the vehicles in that region. To that end, we selected four regions and monitored simultaneously the speed, fuel consumption and emissions of CO2, CO and NOx from a fleet of 15 buses of the same technology during eight months of normal operation. The driving patterns exhibited by drivers in each region were described in terms of 23 characteristic parameters (CPs) such as average speed and average positive kinetic energy. Then, for each region, we constructed their DC using the MT method and evaluated how close it describes the observed driving pattern in each region. We repeated the process using the MCMC and FB methods. Given the stochastic nature of MT and MCMC methods, the DCs obtained changed every time the methods were applied. Hence, we repeated the process of constructing the DCs up to 1000 times and reported their average relative differences and dispersion. We observed that the FB method exhibited the best performance producing DCs that describe the observed driving patterns. In all the regions considered in this study, the DCs produced by this method showed average relative differences smaller than 20% for all the CPs considered. A similar performance was observed for the case of fuel consumption and emission of pollutants.

scholarly journals The Effect of Driving Cycle Duration on its Representativeness

2021 ◽  
Vol 12 (4) ◽  
pp. 212
Author(s):  
Michael Giraldo ◽  
Luis F. Quirama ◽  
José I. Huertas ◽  
Juan E. Tibaquirá
Keyword(s):  
Time Series ◽  
Energy Consumption ◽  
Fuel Consumption ◽  
Driving Cycle ◽  
Cycle Duration ◽  
Characteristic Parameters ◽  
Traffic Conditions ◽  
Driving Patterns ◽  
Driving Pattern ◽  
Fuel Consumption And Emissions

There is an increasing interest in properly representing local driving patterns. The most frequent alternative to describe driving patterns is through a representative time series of speed, denominated driving cycle (DC). However, the DC duration is an important factor in achieving DC representativeness. Long DCs involve high testing costs, while short DCs tend to increase the uncertainty of the fuel consumption and tailpipe emissions results. There is not a defined methodology to establish the DC duration. This study aims to study the effect of different durations of the DCs on their representativeness. We used data of speed, time, fuel consumption, and emissions obtained by monitoring for two months the regular operation of a fleet of 15 buses running in two flat urban regions with different traffic conditions. Using the micro-trips method, we constructed DCs with a duration of 5, 10, 15, 20, 25, 30, 45, 60, and 120 min for each region. For each duration, we repeated the process 500 times in order to establish the trend and dispersion of the DC characteristic parameters. The results indicate that to obtain driving pattern representativeness, the DCs must last at least 25 min. This duration also guarantees the DC representativeness in terms of energy consumption and tailpipe emissions.

scholarly journals A Modified ABC-SQP-Based Combined Approach for the Optimization of a Parallel Hybrid Electric Vehicle

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4529
Author(s):  
S. N. Shivappriya ◽  
S. Karthikeyan ◽  
S. Prabu ◽  
R. Pérez de Pérez de Prado ◽  
B. D. Parameshachari
Keyword(s):  
Boundary Conditions ◽  
Fuel Consumption ◽  
Hybrid Electric Vehicle ◽  
Test Procedure ◽  
Heuristic Approach ◽  
Emissions Control ◽  
Driving Cycles ◽  
Parallel Hybrid ◽  
Hybrid Electric ◽  
Fuel Consumption And Emissions

In this paper, an improved fuel consumption and emissions control strategy based on a mathematical and heuristic approach is presented to optimize Parallel Hybrid Electric Vehicles (HEVs). The well-known Sequential Quadratic Programming mathematical method (SQP-Hessian approach) presents some limitations to achieve fuel consumption and emissions control optimization, as it is not able to find the global minimum, and it generally shows efficient results in local exploitation searches. The usage of a combined Modified Artificial Bee Colony algorithm (MABC) with the SQP approach is proposed in this work to obtain better optimal solutions and overcome these limitations. The optimization is performed with boundary conditions, considering that the optimized vehicle performance has to satisfy Partnership for a New Generation of Vehicles (PNGV) constraints. The weighting factor of the vehicle’s performance parameters in the objective function is varied, and optimization is carried out for two different driving cycles, namely Federal Test Procedure (FTP) and Economic commission Europe—Extra Urban Driving Cycle (ECE-EUDC), using the MABC and MABC with SQP approaches. The MABC with SQP approach shows better performance in terms of fuel consumption and emissions than the pure heuristic approach for the considered vehicle with similar boundary conditions. Moreover, it does not present significant penalties for final battery charging and it offers an optimized size of the key vehicle’s components for different driving cycles.

scholarly journals Comparison of fuel consumption and exhaust emissions in WLTP and NEDC procedures

2019 ◽  
Vol 179 (4) ◽  
pp. 186-191
Author(s):  
Grzegorz KOSZAŁKA ◽  
Andrzej SZCZOTKA ◽  
Andrzej SUCHECKI
Keyword(s):  
European Commission ◽  
Fuel Consumption ◽  
Test Procedure ◽  
Real Life ◽  
Exhaust Emissions ◽  
Driving Cycle ◽  
The Other ◽  
Toxic Compounds ◽  
The Third ◽  
Driving Cycles

Fuel consumption achieved in the New European Driving Cycle (NEDC) could be 50% lower than the fuel consumption in real driving conditions and in the case of emissions of regulated toxic compounds the differences could even be much greater. In order to bring the results achieved in official tests closer to real life figures, the European Commission introduced in 2017 the Worldwide Harmonized Light Vehicles Test Procedure (WLTP), which replaced the NEDC. In this article the results of fuel consumption and exhaust emissions for 3 cars fitted with engines of the same displacement but with direct and indirect gasoline injection, determined according to the NEDC and WLTC were presented. The results show that the effect of driving cycle on the fuel consumption is equivocal – for one car, fuel consumption was higher in the WLTC; for the other one in the NEDC; and for the third one, fuel consumption achieved in both driving cycles was practically the same. Emissions of regulated exhaust compounds, except for THC, obtained in the WLTC were higher than in the NEDC driving cycle.

scholarly journals myBas driving cycle for Kuala Terengganu city

2021 ◽  
Vol 11 (3) ◽  
pp. 2054
Author(s):  
J. S. Norbakyah ◽  
M. I. Nordiyana ◽  
I. N. Anida ◽  
A. F. Ayob ◽  
A. R. Salisa
Keyword(s):  
Fuel Consumption ◽  
Driving Cycle ◽  
Vehicle Speed ◽  
Clustering Method ◽  
Time Data ◽  
Driving Cycles ◽  
Data Points ◽  
Vehicle Simulator ◽  
Trunk Routes ◽  
Fuel Consumption And Emissions

Driving cycles are series of data points that represent vehicle speed versus time sequenced profile developed for specific road, route, city or certain location. It is widely utilized in the application of vehicle manufacturers, environmentalists and traffic engineers. Since the vehicles are one of the higher air pollution sources, driving cycle is needed to evaluate the fuel consumption and exhaust emissions. The main objectives in this study are to develop and characterize the driving cycle for myBAS in Kuala Terengganu city using established k-means clustering method and to analyse the fuel consumption and emissions using advanced vehicle simulator (ADVISOR). Operation of myBAS offers 7 trunk routes and one feeder route. The research covered on two operation routes of myBAS which is Kuala Terengganu city-feeder and from Kuala Terengganu to Jeti Merang where the speed-time data is collected using on-board measurement method. In general, driving cycle is made up of a few micro-trips, defined as the trip made between two idling periods. These micro-trips cluster by using the k-means clustering method and matrix laboratory software (MATLAB) is used in developing myBAS driving cycle. Typically, developing the driving cycle based on the real-world in resulting improved the fuel economy and emissions of myBAS.

Different Configurations of Exhaust Gas Heat Recovery in Internal Combustion Engine: Evaluation on Different Driving Cycles Using Numerical Simulations

2018 ◽  
Vol 10 (4) ◽  
Author(s):  
Hanna Sara ◽  
David Chalet ◽  
Mickaël Cormerais
Keyword(s):  
Numerical Simulations ◽  
Fuel Consumption ◽  
Heat Recovery ◽  
Combustion Engine ◽  
Management Strategies ◽  
Driving Cycle ◽  
Maximum Temperature ◽  
Exhaust Gas ◽  
Direct Heating ◽  
Driving Cycles

Exhaust gas heat recovery is one of the interesting thermal management strategies that aim to improve the cold start of the engine and thus reduce its fuel consumption. In this work, an overview of the heat exchanger used as well as the experimental setup and the different tests will be presented first. Then numerical simulations were run to assess and valorize the exhaust gas heat recovery strategy. The application was divided into three parts: an indirect heating of the oil with the coolant as a medium fluid, a direct heating of the oil, and direct heating of the oil and the coolant. Different ideas were tested over five different driving cycles: New European driving cycle (NEDC), worldwide harmonized light duty driving test cycle (WLTC), common Artemis driving cycle (CADC) (urban and highway), and one in-house developed cycle. The simulations were performed over two ambient temperatures. Different configurations were proposed to control the engine's lubricant maximum temperature. Results concerning the temperature profiles as well as the assessment of fuel consumption were stated for each case.

Traffic Condition-Based Gain Scheduling of Electric Assist Control Strategy for Parallel Hybrid Electric Vehicles

2007 ◽  
Author(s):  
Amir Poursamad
Keyword(s):  
Fuel Consumption ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Hybrid Electric Vehicles ◽  
Gain Scheduling ◽  
Driving Cycle ◽  
Traffic Condition ◽  
Traffic Conditions ◽  
Parallel Hybrid ◽  
Fuel Consumption And Emissions

This paper presents gain scheduling of control strategy for parallel hybrid electric vehicles based on the traffic condition. Electric assist control strategy (EACS) is employed with different parameters for different traffic conditions. The parameters of the EACS are optimized and scheduled for different traffic conditions of TEH-CAR driving cycle. TEH-CAR is a driving cycle which is developed based on the experimental data collected from the real traffic condition in the city of Tehran. The objective of the optimization is to minimize the fuel consumption and emissions over the driving cycle, while enhancing or maintaining the driving performance characteristics of the vehicle. Genetic algorithm (GA) is used to solve the optimization problem and the constraints are handled by using penalty functions. The results from the computer simulation show the effectiveness of the approach and reduction in fuel consumption and emissions, while ensuring that the vehicle performance is not sacrificed.

The development of a driving cycle for fuel consumption and emissions evaluation

1986 ◽  
Vol 20 (6) ◽  
pp. 447-462 ◽  
Author(s):  
T.J. Lyons ◽  
J.R. Kenworthy ◽  
P.I. Austin ◽  
P.W.G. Newman
Keyword(s):  
Fuel Consumption ◽  
Driving Cycle ◽  
Fuel Consumption And Emissions

Evaluation of hot water storage strategy in internal combustion engine on different driving cycles using numerical simulations

2017 ◽  
Vol 232 (8) ◽  
pp. 1019-1035 ◽  
Author(s):  
Hanna Sara ◽  
David Chalet ◽  
Mickaël Cormerais ◽  
Jean-François Hetet
Keyword(s):  
Ambient Temperature ◽  
Fuel Consumption ◽  
Thermal Management ◽  
Negative Impact ◽  
Combustion Engine ◽  
Driving Cycle ◽  
Hot Water ◽  
Pollutant Emissions ◽  
Engine Model ◽  
Driving Cycles

Since the main interest worldwide of green environment companies is to reduce pollutant emissions, the automotive industry is aiming to improve engine efficiency in order to reduce fuel consumption. Recently, studies have been shifted from upgrading the engine to the auxiliary systems attached to it. Thermal management is one of the successful fields that has shown promise in minimizing fuel consumption and reducing pollutant emissions. Throughout this work, a four-cylinder turbocharged diesel engine model was developed on GT-Power. Also, a thermal code has been developed in parallel on GT-Suite, in which the different parts of the coolant and lubricant circuits were modeled and calibrated to have the best agreement with the temperature profile of the two fluids in the system. Once the model was verified, hot coolant storage, a thermal management strategy, was applied to the system to assess the fuel consumption gain. The storage tank was located downstream the thermostat and upstream the radiator with three valves to control the coolant flow. The place was chosen to avoid negative impact on the cold start-up of the engine when the tank is at the ambient temperature. This strategy was applied on different driving cycles such as the NEDC, WLTC, CADC (urban and highway), and an in-house developed driving cycle. The ambient temperature was varied between −7°C to represent the coldest winter and 20°C. The results of this study summarize the ability of the hot coolant storage strategy in reducing the fuel consumption, and show the best driving cycle that needs to be applied on along with the influence of the different ambient temperatures.

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