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Evaluation Method for HDV Fuel Economy Performance with PC Simulation and Mapping Procedure

A. Noda, Yujiro Tsukamoto, Tatsuji Sato, Hiroyuki Yagi

Open publisher page 6 citations

Abstract

As countermeasures against global warming caused by carbon dioxide, improvement of automotive fuel economy to lower CO2 emission becomes important. In order to promote less CO2 vehicles, appropriate methods to evaluate vehicle fuel economy performance are needed. However, the existing fuel economy test is limited to passenger cars and light duty trucks. The test is executed on a chassis dynamometer. However, if this test method is applied to heavy-duty vehicles (HDV), a large sized chassis dynamometer is needed. Furthermore, heavy duty vehicles have wide variations in a combination of an equipped engine, body shape, a transmission gear, a permissible limit of pay load, and so on. This leads to the increase in the number of chassis dynamometer tests. Therefore, it is difficult to use chassis dynamometer test to evaluate HDV fuel economy performance. In this study, instead of chassis dynamometer tests, the authors investigated other practical methods that to estimate HDV fuel consumption performance. Consequently, a new method characterized by the combination of two procedures was developed. One procedure is to make an engine fuel consumption map measured with an engine test stand, and the other is to execute a computer simulation procedure. For the first procedure to make the fuel consumption map, the test engine is operated under various steady state driving conditions, which are adjusted by a control system for engine torque and engine speed, and fuel consumption rate (l/h) is measured directly for each driving condition. The role of computer simulation is to calculate sequential engine torque, engine speed and a rate of fuel flow throughout virtual mode driving. For this procedure, the authors designed the computing algorithm that converts speed profile of the given test mode into engine speed and engine torque for each HDV. The accomplished program fulfills some functions, for instance, it can automatically determine suitable gear position and gearshift timing for virtual driving according to mode speed profile and some parameters such as vehicle weight, maximum payload, engine maximum torque curve, gear ratios, and so on. Using gearshift position thus obtained, mode speed profile, and other vehicle parameters, the simulation program calculates engine torque [T] and engine speed [N] of every interval point. Those calculated data [T,N] are applied to the fuel consumption map to compute instantaneous fuel flow rate of each interval point. Interpolation/extrapolation procedure is used for this calculation. Repeating this routine throughout the virtual mode driving and accumulating the data of instantaneous fuel flow rate, the simulation estimates total fuel consumption quantity. The authors examined accuracy and effectiveness of the simulation method. For this purpose, a lot of experiments using an engine stand test and a chassis dynamometer test were conducted. Simulation data of fuel consumption on virtual mode driving was compared with experimental data directly measured with using the same mode. Consequently, it was found that the computed fuel economy data have a good agreement with corresponding experimental data. Therefore, we concluded that the simulation method to evaluate HDV fuel economy performance has effectiveness for various driving conditions.

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What this paper is about

As countermeasures against global warming caused by carbon dioxide, improvement of automotive fuel economy to lower CO2 emission becomes important. In order to promote less CO2 vehicles, appropriate methods to evaluate vehicle fuel economy performance are needed. However, the existing fuel economy test is limited to passenger cars and light duty trucks. The test is executed on a chassis dynamometer. However, if this test method is applied to heavy-duty vehicles (HDV), a large sized chassis dynamometer is needed. Furthermore, heavy duty vehicles have wide variations in a combination of an equipped engine, body shape, a transmission gear, a permissible limit of pay load, and so on. This leads to the increase in the number of chassis dynamometer tests. Therefore, it is difficult to use chassis dynamometer test to evaluate HDV fuel economy performance. In this study, instead of chassis dynamometer tests, the authors investigated other practical methods that to estimate HDV fuel consumption performance. Consequently, a new method characterized by the combination of two procedures was developed. One procedure is to make an engine fuel consumption map measured with an engine test stand, and the other is to execute a computer simulation procedure. For the first procedure to make the fuel consumption map, the test engine is operated under various steady state driving conditions, which are adjusted by a control system for engine torque and engine speed, and fuel consumption rate (l/h) is measured directly for each driving condition. The role of computer simulation is to calculate sequential engine torque, engine speed and a rate of fuel flow throughout virtual mode driving. For this procedure, the authors designed the computing algorithm that converts speed profile of the given test mode into engine speed and engine torque for each HDV. The accomplished program fulfills some functions, for instance, it can automatically determine suitable gear position and gearshift timing for virtual driving according to mode speed profile and some parameters such as vehicle weight, maximum payload, engine maximum torque curve, gear ratios, and so on. Using gearshift position thus obtained, mode speed profile, and other vehicle parameters, the simulation program calculates engine torque [T] and engine speed [N] of every interval point. Those calculated data [T,N] are applied to the fuel consumption map to compute instantaneous fuel flow rate of each interval point. Interpolation/extrapolation procedure is used for this calculation. Repeating this routine throughout the virtual mode driving and accumulating the data of instantaneous fuel flow rate, the simulation estimates total fuel consumption quantity. The authors examined accuracy and effectiveness of the simulation method. For this purpose, a lot of experiments using an engine stand test and a chassis dynamometer test were conducted. Simulation data of fuel consumption on virtual mode driving was compared with experimental data directly measured with using the same mode. Consequently, it was found that the computed fuel economy data have a good agreement with corresponding experimental data. Therefore, we concluded that the simulation method to evaluate HDV fuel economy performance has effectiveness for various driving conditions.

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Available abstract

As countermeasures against global warming caused by carbon dioxide, improvement of automotive fuel economy to lower CO2 emission becomes important. In order to promote less CO2 vehicles, appropriate methods to evaluate vehicle fuel economy performance are needed. However, the existing fuel economy test is limited to passenger cars and light duty trucks. The test is executed on a chassis dynamometer. However, if this test method is applied to heavy-duty vehicles (HDV), a large sized chassis dynamometer is needed. Furthermore, heavy duty vehicles have wide variations in a combination of an equipped engine, body shape, a transmission gear, a permissible limit of pay load, and so on. This leads to the increase in the number of chassis dynamometer tests. Therefore, it is difficult to use chassis dynamometer test to evaluate HDV fuel economy performance. In this study, instead of chassis dynamometer tests, the authors investigated other practical methods that to estimate HDV fuel consumption performance. Consequently, a new method characterized by the combination of two procedures was developed. One procedure is to make an engine fuel consumption map measured with an engine test stand, and the other is to execute a computer simulation procedure. For the first procedure to make the fuel consumption map, the test engine is operated under various steady state driving conditions, which are adjusted by a control system for engine torque and engine speed, and fuel consumption rate (l/h) is measured directly for each driving condition. The role of computer simulation is to calculate sequential engine torque, engine speed and a rate of fuel flow throughout virtual mode driving. For this procedure, the authors designed the computing algorithm that converts speed profile of the given test mode into engine speed and engine torque for each HDV. The accomplished program fulfills some functions, for instance, it can automatically determine suitable gear position and gearshift timing for virtual driving according to mode speed profile and some parameters such as vehicle weight, maximum payload, engine maximum torque curve, gear ratios, and so on. Using gearshift position thus obtained, mode speed profile, and other vehicle parameters, the simulation program calculates engine torque [T] and engine speed [N] of every interval point. Those calculated data [T,N] are applied to the fuel consumption map to compute instantaneous fuel flow rate of each interval point. Interpolation/extrapolation procedure is used for this calculation. Repeating this routine throughout the virtual mode driving and accumulating the data of instantaneous fuel flow rate, the simulation estimates total fuel consumption quantity. The authors examined accuracy and effectiveness of the simulation method. For this purpose, a lot of experiments using an engine stand test and a chassis dynamometer test were conducted. Simulation data of fuel consumption on virtual mode driving was compared with experimental data directly measured with using the same mode. Consequently, it was found that the computed fuel economy data have a good agreement with corresponding experimental data. Therefore, we concluded that the simulation method to evaluate HDV fuel economy performance has effectiveness for various driving conditions.

Key concepts: Computer science, Fuel cells, Engineering, Chemical engineering

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