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A major issue of battery electric vehicles (BEV) is optimizing driving range and energy consumption. Under actual driving, transient thermal and electrical performance changes could deteriorate the battery cells and pack. These performances can be investigated and controlled efficiently with a thermal management system (TMS) via model-based development. A complete battery pack contains multiple cells, bricks, and modules with numerous coolant pipes and flow channels. However, such an early modeling stage requires detailed cell geometry and specifications to estimate the thermal and electrochemical energies of the cell, module, and pack. To capture the dynamic performance changes of the LIB pack under real driving cycles, the thermal energy flow between the pack and its TMS must be well predicted. This study presents a BTMS model development and validation method for a 75-kWh battery pack used in mass-production, mid-size battery SUV under WLTC.

Performances of battery electric vehicles (BEV) are affected by the thermal imbalance in the battery packs under driving cycles. BEV thermal management system (VTMS) should be managed efficiently for optimal energy consumption and cabin comfort. Temperature changes in the brick, module, and pack under the repeated transient cycles must be understood for model-based development. The authors conducted chassis dynamometer experiments on a fully electric small crossover sports utility vehicle (SUV) to address this challenge. A BEV is tested using a hub-type, 4-wheel motor chassis dynamometer with an air blower under the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) and Federal Test Procedures (FTP) with various ambient temperatures. The mid-size BEV with dual-motor featured 80 thermocouples mounted on the 74-kWh battery pack, including the cells, upper tray, side cover, and pack cover.

Battery thermal management system (BTMS) significantly improves battery electric vehicle (BEV) performance, especially under cold weather. A tradeoff between battery power consumption and cabin heating performance must be considered in cold driving conditions. This preliminary study aims to develop an integrated battery pack and coolant channel model to predict the thermal behavior of a BEV thermal management system. In this study, we develop and calibrate the physical baseline model with testbench data using finite element and CFD software. First, an electrochemical battery cell 1D model (Pseudo-2D or P2D) is built and calibrated against the cell reference data. An integrated pack model consisting of four modules (each has 23 and 25 bricks and a total of 4416 cells) with coolant flow channels is developed using reference and benchmarked data.

Synthetic fuels can significantly improve the combustion and emission characteristics of heavy-duty diesel engines toward decarbonizing heavy-duty propulsion systems. This work analyzes the effects of engine operating conditions and synthetic fuel properties on spray, combustion, and emissions (soot, NOx) using a supercharging single-cylinder engine experiment and KIVA-4 code combined with CHEMKIN-II and in-house phenomenological soot model. The blended fuel ratio is fixed at 80% diesel and 20% n-paraffin by volume (hereafter DP). Diesel, DP1 (diesel with n-pentane C5H12), DP2 (diesel with n-hexane C6H14), and DP3 (diesel with n-heptane C7H16) are used in engine-like-condition constant volume chamber (CVC) and engine experiments. Boosted engine experiments (1080 rpm, common-rail injection pressure 160 MPa, multi-pulse injection) are performed using the same DP fuel groups under various main injection timings, pulse-injection intervals, and EGR = 0-40%.

Alternative propulsion systems such as renewable fuels and electric powertrains are expensive; thus, efficient internal combustion engines (ICE) with hybrid powertrains still play significant roles in the transportation fleet in the coming decades. Modern engine technologies have been adopted to meet stringent emissions and fuel economy standards. As a result, engine control systems are becoming more complex. Furthermore, as ICE control parameters increase exponentially, engine calibration and design become bottlenecks in the development process. While a map-based feed-forward control method is a current de facto standard in combustion control, online closed-loop feedback control can improve engine performance and robustness. However, adding physical sensors to measure the various data for the online feedback control and calibration increase the vehicle cost.

A swirl-chamber diesel engine has an indirect injection system in which fuel is injected into a pre-chamber called the swirl-chamber that is separated from the main chamber. Indirect fuel injection systems can be directly mechanically controlled by the camshaft, which is cheaper than electronic control. For these reasons, they are used in diverse industrial applications and automobiles. However, optimization of the swirl-chamber shape and performance tests have been mainly experimental, and there has been insufficient verification of the accuracy of simulations. Thus, we have attempted to verify simulations using a rapid compression and expansion machine that can reproduce the combustion in one engine cycle, with a chamber like a swirl chamber in the cylinder head to visualize the behavior of evaporative sprays and the combustion process. In this study, the authors focused on the wall impingement of the fuel spray and took photos of its liquid phase and ignition.

For a series hybrid electric vehicle (SHEV), the electric motor is responsible for driving the wheels, while the engine drives the only generator to provide electricity. SHEVs set a control strategy to make the engine run near the fixed operating point with high thermal efficiency, thereby effectively reducing fuel consumption. The powertrain system of HEV is more complex than that of a conventional drive system using only an internal combustion engine, and it is time-consuming to obtain the optimal components specification values and control parameters. Therefore, automatic optimization methods are required nowadays. We used Genetic Algorithm (GA) as the optimization method and optimize powertrain specifications and control parameter values to reduce fuel consumption. The results show that it is an effective optimization method.

This paper describes the development of an integrated simulation model for evaluating the effects of electrically heating the three-way catalyst (TWC) in a series hybrid electric vehicle (s-HEV) on fuel economy and exhaust gas purification performance. Engine and TWC models were developed in GT-Power to predict exhaust emissions during transient operation. These models were validated against data from vehicle tests using a chassis dynamometer and integrated into an s-HEV model built in MATLAB/Simulink. The s-HEV model accurately reproduced the performance characteristics of the vehicle’s engine, motor, generator, and battery during WLTC mode operation. It can thus be used to predict the fuel consumption, emissions, and performance of individual powertrain components. The engine combustion characteristics were reproduced with reasonable accuracy for the first 50 combustion cycles, representing the cold-start condition of the driving mode.

Performance predictions of advanced turbocharged engines are becoming difficult because conventional engine models are built using performance map data of turbochargers with a proportional integral derivative (PID) controller. Improving prediction capabilities under transient test cycles or real driving conditions is a challenging task. This study applies a machine learning technique to predict turbocharger performances with high accuracy under steady-state and transient conditions. The manipulated signals of engine speed and torque created based on Compressed High-Intensity Radiated Pulse (Chirp signal) and Amplitude-modulated Pseudo-Random Binary Signal (APRBS) are used as inputs to the engine testbed. Data from the engine experiments are used as training data for the AI-based turbocharger model. High prediction accuracy of the AI turbocharger model is achieved with the co-efficient of determination in the model, and cross-validation results are higher than 0.8.

Emission regulations are becoming tighter, and Real Driving Emissions (RDE) is proposed as a testing cycle for evaluating modern engine emissions under a wide operation range. For this reason, engine manufacturers have been developing a method to effectively assess engine performances and emissions under a wide range of transient conditions. Transient engine performances can be evaluated efficiently by applying time-series data created by chirp signals. However, when the time-series data produced by the chirp signal are used directly, the engine hardware may damage, and emission performances deteriorate drastically. It is therefore essential to develop a method to avoid these undesirable operating conditions. This work aims to develop an algorithm to avoid such unrealistic operation conditions for engine performance evaluation. A virtual diesel engine (VDE) model is developed based on a four-cylinder engine using GT-POWER software.

To prevent global warming, further reductions in carbon dioxide are required. It is therefore important to promote the spread of electric vehicles powered by internal combustion engines and electric vehicles without internal combustion engines. As a result, emissions from hybrid electric vehicles equipped with internal combustion engines should be further reduced. Interest in catalytic reactions in an electric field with a higher catalytic activity compared to conventional catalysts has increased because this technology consumes less energy than other electrical heating devices. This study was therefore undertaken to apply a catalytic reaction in an electric field to an exhaust emission control. First, the original experimental equipment was built with a high voltage system used to conduct catalytic activity tests.

Battery models are being developed as a component of the powertrain systems of hybrid electric vehicles (HEVs) to predict the state of charge (SOC) accurately. Electrically heated catalysts (EHCs) can be employed in the powertrains of HEVs to reach the catalyst light off temperature in advance. However, EHCs draw power from the battery pack and hence sufficient energy needs to be stored to power auxiliary components. In series HEVs, the engine is primarily used to charge the battery pack. Therefore, it is important to develop a control strategy that triggers engine start/stop conditions and reduces the frequency of engine operation to minimize the equivalent fuel consumption. In this study, a battery pack model was constructed in MATLAB-Simulink to investigate the SOC variation of a high-power lithium ion battery during extreme engine cold start conditions (-7°C) with/without application of an EHC.

To identify ways of achieving good mixture formation and heat release in diesel spray combustion, we have performed Large Eddy Simulation (LES) using a detailed chemical reaction mechanism to study the temporal and spatial distribution of the local equivalence ratios and heat release rate. Here we characterize the effect of the fuel injection rate profile on these processes in the combustion chamber of a diesel engine. Two injection rate profiles are considered: a standard (STD) profile, which is a typical modern common rail injection profile, and the inverse delta (IVD) profile, which has the potential to suppress rich mixture formation in the spray tip region. Experimental data indicate that the formation of such mixtures may extend the duration of the late combustion period and thus reduce thermal efficiency.

Pre-chamber spark ignition technology can stabilize combustion and improve thermal efficiency of lean burn natural gas engines. During compression stroke, a homogeneous lean mixture is introduced into pre-chamber, which separates spark plug electrodes from turbulent flow field. After the pre-chamber mixture is ignited, the burnt jet gas is discharged through multi-hole nozzles which promotes combustion of the lean mixture in the main chamber due to turbulence caused by high speed jet and multi-points ignition. However, details mechanism in the process has not been elucidated. To design the pre-chamber geometry and to achieve stable combustion under the lean condition for such engines, it is important to understand the fundamental aspects of the combustion process. In this study, a high-speed video camera with a 306 nm band-pass filer and an image intensifier is used to visualize OH* self-luminosity in rapid compression-expansion machine experiment.

A new engine concept based on pulsed supermulti-jets colliding at a small area around the chamber center was proposed in our previous research. It was expected to provide noiseless high compression ratio and nearly-complete air-insulation on chamber walls, leading to high thermal efficiency. In the previous reports, three-dimensional computations for the unsteady compressible Navier-Stokes equation were conducted, which were qualitative because of using regular grid method. This time, we develop a new numerical code in order to quantitatively simulate the compression level caused by the jets colliding with pulse. It is achieved by applying a staggered grid method to improve conservatibity of physical quantities at very high compression in combustion phenomena. Computations at a simple condition were fairly agreed with a theoretical value. Computational results obtained for a complex geometry of an engine by the new code had less error than one with previous codes.

Cars with diesel engines are commonly equipped with a Diesel Particulate Filter (DPF) to reduce their emissions of particulate matter (PM). Because the pressure drop within the DPF reduces engine performance, it must be predicted with accuracy. The purpose of this study was to improve the accuracy of a DPF simulation model under transient conditions by parameter optimization. The DPF model under consideration consists of an inlet channel, a cake layer, wall layer, and an outlet channel. The pressure drop is influenced by the location, mass, and density of the deposited soot. Therefore, the model includes the following sub-models: Sub-model 1: Calculates the soot density deposited in the wall layer Sub-model 2: Computes the filtration efficiency and mass of the wall and cake layer Sub-model 3: Calculates the soot density deposited in the cake layer Because the sub-models include some empirical formulae, the first step in refining the model was to optimize their fitting parameters.

A mixed timescale subgrid model of a large eddy simulation was used to simulate the turbulence regime in diesel engine combustion. The combustion model used the direct integration approach with a diesel oil surrogate mechanism (developed at Chalmers University of Technology and consisting of 70 species and 309 reactions). Additional reactions for the generation and consumption of OH*, CO2*, and CH* species were added from recent kinetic studies. Collisional quenching and spontaneous emission resulted in de-excitation of the excited state radical. A phenomenological soot formation model (developed at Waseda University) was combined with the LES code. The following important steps were considered in the soot model: particle inception where naphthalene grows irreversibly to form soot, surface growth with the addition of C2H2, surface oxidation (induced by OH radicals and O2 attack), and particle coagulation.

Much effort has been devoted to studies on auto-ignition engines of gasoline including homogeneous-charge combustion ignition engines over 30 years, which will lead to lower exhaust energy loss due to high-compression ratio and less dissipation loss due to throttle-less device. However, the big problem underlying gasoline auto-ignition is knocking phenomenon leading to strong noise and vibration. In order to overcome this problem, we propose the principle of colliding pulsed supermulti-jets. In a prototype engine developed by us, octagonal pulsed supermulti-jets collide and compress the air around the center point of combustion chamber, which leads to a hot spot area far from chamber walls. After generating the hot spot area, the mechanical compression of an asymmetric double piston unit is added in four-stroke operation, which brings auto-ignition of gasoline.

In our previous papers, a new concept of a compressive combustion engine (Fugine) was proposed based on the collision of pulsed supermulti-jets, which can enclose the burned gas around the chamber center leading to an air-insulation effect and also a lower exhaust gas temperature due to high single-point compression. In order to examine the compression level and air-insulation effect as basic data for application to automobiles, aircraft, and rockets, a prototype engine based on the concept, i.e., a piston-less prototype engine with collision of bi-octagonal pulsed multi-jets from fourteen nozzles, was developed. Some combustion results [Naitoh et al. SAE paper, 2016] were recently reported. However, there was only one measurement of wall temperature and pressure in the previous report. Thus, in this paper, more experimental data for pressures and temperatures on chamber walls and exhaust temperatures, are presented for the prototype engine.

Computational and theoretical analyses for a new type of engine (Fugine), which was proposed by us based on the colliding of pulsed supermulti-jets, indicate a potential for very high thermal efficiencies and also less combustion noise. Three types of prototype engines were developed. One of them has a low-cost gasoline injector installed in the suction port and a double piston system in which eight octagonal supermulti-jets are injected and collide. Combustion experiments conducted on the prototype gasoline engine show high thermal efficiency comparable to that of diesel engines and less combustion noise comparable to that of traditional spark-ignition gasoline engines. This paper presents some combustion experiments of one of the other piston-less prototype engines having bi-octagonal pulsed multi-jets injected from fourteen nozzles.