Development of Energy Balance Simulation Method for Vehicles

Transcription

1 New technologies Development of Energy Balance Simulation Method for Vehicles Shigeyoshi Kadokura* Daisuke Konno* Hiroshi Ezaki* Kazunori Sekine** Chiharu Katsuyama** Tomohiro Nishizawa** Abstract In recent years, many kinds of onboard systems are required to minimize their energy consumption. To develop these items, it is important to clarify energy flow dynamics within the vehicle systems. In the previous report, we developed the energy balance simulation method for electric vehicles, which can calculate energy in/out flows between onboard subsystems. This time, we have developed a simulation method for internal combustion engine vehicles, whose energy flow is more complex than that of electric vehicles. This article describes the simulation method with calculation examples and experimental validation results. Key Words : simulation, energy management, heat management, MATLAB, Simulink, air conditioning 1. Background In recent years, efficient use of energy in a car is expected for improving fuel economy. Specifically, (1) improving system efficiency, and (2) retaining wasted energy and utilizing it for another usage are considered. It will be necessary to quantify the energy state in each part of a vehicle under all running conditions to realize (1) and (2). However, energy distribution changes due to environmental conditions. A vehicle has various on-board systems, each of which influences other system s operational conditions. For instance, Fig. 1 illustrated significant difference of the energy distribution provided from an engine between in summer (a) and in winter (b) conditions. This indicates that quantification of vehicle energy includes balance calculations through tracking multiple systems behavior/state in various scenes considering factors such as outside temperature and driving style. (a) Energy distribution in summer (b) Energy distribution in winter Fig. 1 Energy distribution of vehicle system 2. Specific Problems and Measures In the previous paper (1)(2) we reported that we had been able to calculate energy balance in electric vehicles through developing new simulation models of motors and batteries, and integrating them with the existing simulation models of CalsonicKansei products. Meanwhile, it is expected that vehicles with an internal combustion engine (ICE) will remain major in the market, thus improving fuel economy for these ICE-based vehicles continues to be important. Since engine-related components were not included in the above simulation model, we needed to develop a new engine model for studying fuel economy improvement for ICE-based vehicles. This simulation method was also necessary to be able to instantly calculate the balance between an engine and other multiple systems. Fig. 2 shows the concept of calculating methods for electric vehicles and ICE-based vehicles. The electricity * Global Technology Division Green Technology Development Group ** Global Technology Division CAE Analysis Group 39

2 CALSONIC KANSEI TECHNICAL REVIEW vol consumption of an electric vehicle is obtained by adding up the energy each system requires of a battery. On an ICE-based vehicle, engine speed and engine power are influenced by not only running condition but also the operative condition of each component. This means that the calculation of fuel consumption requires identifying the balanced point between the engine and each component or system. For example, a change in an operational condition of a single system will cause a change in all other operation points in the vehicle system via the engine, which demands more complex and time-consuming calculations than those for electric vehicles. Fig. 2 Conceptual diagram of vehicle simulation Considering these factors in building the model for ICEbased vehicles, we carefully designed the calculation steps and the parameter choices, which highly affect calculation speed and subsequently development speed in the future. 3. Simulation Model We used AMESim, a one-dimensional physical analysis software, and MATLAB /Simulink for building the simulation model. AMESim was used for the models of engine, transmission, air-conditioning (A/C) cycle and accessories. MATLAB /Simulink was used for calculation of cabin temperature and humidity, and speed of A/C winds, then we integrated these models. Shows the entire structure of the simulation models. We also added simple control models on A/C, alternator and transmission to this structure. 3.1 Structure of Vehicle Model As shown in Fig. 3, the developed simulation model consists of two categories of models: sub-system models and component models. A component model represents an engine, a transmission or other parts and is comprised of certain mathematical expressions of the part s characteristics and governing physical phenomenon. Part characteristics includes static one such as dimension, surface area, thermophysical property and mass, and dynamic performance such as efficiency, air flow rate and air pressure drop. A sub-system model is comprised of component models and control models. The sub-system models and the component models are designed to reflect the other model s data on their calculation results to determine the balanced point. This made it possible to calculate the direction and the quantity of energy transfer, system performance, and the temperature in operating state. The next section explains power train model, which plays a central role in the modeling of ICE-based vehicles. Fig. 3 Structure of energy balance simulation 40

3 Development of Energy Balance Simulation Method for Vehicles Fig. 4 Calculation diagram of engine and transmission 3.2 Details of Powertrain Model Powertrain model consists of an engine to calculate power and fuel consumption, and a transmission to control the gear ratio. AMESim has an advantage of easy model building and parameter setting with pre-provided standardized component models and even demo-models as examples. This powertrain model enabled calculation of driving force and fuel consumption. The following describes the procedures and the parameters applied for the powertrain model development. (1) Engine (Fig. 3 *1, Fig. 4*1) A map type model is used for the engine model. According to driver s throttle opening ratio, coolant temperature and engine revolutions speed, this calculation model refers to multiple maps to determine the output. The following 2 to 6 describe the maps necessary for this model. (2) BMEP (Brake Mean Effective Pressure, Fig. 4 Ⅱ) This parameter stands for output characteristics of the engine (net effective average pressure) and is calculated based on the engine revolution speed and throttle opening ratio. It can be converted to engine torque by taking displacement into account. In this study, we applied typical engine characteristics. (3) Thermal losses (Fig. 4 Ⅲ) This parameter stands for the rate of energy emitted in the form of heat in the total combustion energy and is calculated from the engine revolution speed and BMEP. It was estimated through measurement of temperature and flow rate of exhaust gas and of coolant, and engine room temperature in a vehicle test under various running loads. (4) Fuel consumption (Fig. 4 Ⅳ) This parameter stands for fuel consumption per unit power of the engine. It is also calculated from the engine revolution speed and BMEP. We identified the map values for a typical vehicle so as to correspond to the result of a vehicle wind tunnel test under several patterns of vehicle speed and acceleration. (5) FMEP (Friction Mean Effective Pressure, Fig. 4 Ⅴ) This parameter stands for friction loss of the engine and is calculated from the engine revolution speed and coolant temperature. This energy is emitted in the form of heat. We adjusted gain in the model so that the maximum engine output at the maximum load corresponds to that of a typical engine characteristics. (6) Transmission (Fig. 4 *2) We measured transmission gear ratio through a road test because the test vehicle in this study was with a CVT-type transmission. Fig. 5 shows the test result. From the result, we created the transmission gear ratio map with the parameters of vehicle speed and throttle opening ratio. 41

4 CALSONIC KANSEI TECHNICAL REVIEW vol Fig. 5 Transmission gear ratio 4. Verification of the Model We compared calculation results using the simulation model with test results and confirmed the validity. We applied the results of a vehicle wind tunnel test for the verification. (b) Fuel consumption Fig. 6 Results of mode drive Table 2 Test condition 4.1 Verification of Running Model We performed a road test under the conditions in Table 1 to verify the model. Fig. 6 (a) and (b) respectively show the running vehicle speed and fuel consumption, which indicate good agreement between calculation and experiment. Table 1 Test condition 4.2 Verification of Air Conditioning System Model Air conditioner largely affects actual fuel consumption of a vehicle. To confirm whether it is possible to use the simulation for problem analysis and solution study to improve fuel consumption performance, we verified the model through cooling/heating tests under the conditions in Table 2. This simulation does not consider heat from the human body nor moisture from exhalation. Fig. 7 shows the compared results of the wind tunnel vehicle test and the simulation in cooling mode. Graph (a) shows the fuel consumption, (b) shows the cabin temperatures and (c) shows the evaporator temperatures. The simulation results of fuel consumption and of evaporator temperatures are very similar to the test results. The increase/decrease in fuel consumption due to turning A/C on/off is also simulated well in this calculation. (a) Vehicle speed 42

5 Development of Energy Balance Simulation Method for Vehicles Fig. 8 shows the compared results of the wind tunnel vehicle test and of the simulation in heating mode. Graph (a) shows the fuel consumption, (b) shows the cabin temperatures and (c) shows the refrigerant temperatures. For air flow rate in the blower, the vehicle test result was used in the simulation. Deviation from the experimental results is observed in the fuel consumption, the cabin temperature, and the refrigerant temperature immediately after the operation start. This could be due to limitation of the simulation that the model does not include gear ratio control to accelerate engine and transmission warm-up during lowtemperature condition. This factor causes the difference in the refrigerant temperature at the initial stage. Also the difference in cabin temperatures may be due to the omission of temperature increase by breathing, heat from a human body, and heat leakage by ram pressure during driving. Further consideration of relevant control of engine and transmission under low temperature would be necessary in the future. (a) Fuel consumption (a) Fuel consumption (b) Cabin temperature (c) Average of evaporator temperature Fig. 7 Results of cooling mode (b) Cabin temperature (c) Water temperature Fig. 8 Results in heating mode 43

6 CALSONIC KANSEI TECHNICAL REVIEW vol Usage Example of the Simulation Technology Though the verification showed that the absolute temperature values are apart from those in vehicle tests, we judged that the simulation can be used for relative comparison and studied the effect of a certain technology measure designed for improving fuel consumption. For a case study of an exhaust-heat-recovery system, which recovers exhaust heat into coolant and accelerates vehicle warming-up, we made calculations under the conditions in Table 3. Fig. 9 shows the calculation results. Graph (a) shows engine outlet coolant temperature, (b) shows transmission oil temperature, and (c) shows fuel consumption. The exhaust-heat-recovery device shortened the warming-up time by about 600 seconds before reaching stable temperature, and raised transmission oil temperature by about 2 at 1200 second point after the simulation start. As a result, the exhaust-heat-recovery device was found to be highly effective for improving fuel consumption, realizing a 4% decrease in the fuel consumption in comparison with the case without the device. The improvement by lowered friction loss in the engine and the transmission is considered to be caused by increased coolant temperature. The above result shows that the use of the exhaust-heat-recovery device is effective for improving fuel consumption in cold engine conditions. 6. Conclusion Based on the previously reported simulation model for electric vehicles (1), further advanced simulation enabling calculation of energy balance for ICE-based vehicles has been developed with integrating the models of an engine and transmission. This simulation model can be used for a wide range applications from electric to ICE-based vehicles in order to efficiently study new designs for improving fuel/ electricity consumption. It is noted that the following points are to be addressed in the future. (1) Further integration of warm-up control algorithm etc. (2) Further detailed vehicle model development (3) Integrating the model with electric systems to enable further study on improving energy consumption by power regeneration or electricity storage. Table 3 Test condition (a) Engine outlet water temperature (b) Transmission oil temperature (c) Fuel consumption Fig. 9 Results of heat recovery system 44

7 Development of Energy Balance Simulation Method for Vehicles References (1) Shigeyoshi KADOKURA, Daisuke KONNO, Hiroshi EZAKI, Kei TAKEUCHI, Kazunori SEKINE, Chiharu KATSUYAMA, and Tomohiro NISHIZAWA (2012). Development of Simulation Technology for Energy Balance in Electric Vehicle,Calsonic Kansei Technical Review vol.9,p60-66 (2) Hiroshi EZAKI, Norihide MIYASHITA, Ryou WATANABE, and Muneaki KAWAMURA (2009). Development of Simulation for Cabin Temperature Distributio,Calsonic Kansei Technical Review v o l. 6 _ ,p Shigeyoshi Kadokura Daisuke Konno Hiroshi Ezaki Kazunori Sekine Chiharu Katsuyama Tomohiro Nishizawa 45