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A dimensionless relationship that estimates the maximum bearing load of a 4-cylinder 4-stroke in-line engine has been found. This relationship may assist the design engineer in choosing a desired counterweight mass. It has been demonstrated that: 1) the average bearing load increases with engine speed and 2) the maximum bearing load initially decreases with engine speed, reaches a minimum, then increases quickly with engine speed. This minimum refers to a transition speed at which the contribution of the inertia force overcomes the contribution of the maximum pressure force to the maximum bearing load. The transition speed increases with an increase of counterweight mass and is a function of maximum cylinder pressure and the operating parameters of the engine.

Conventional CFD analysis for underhood thermal management is quite involved and time consuming because of the complex geometry and flow distributions. As an alternative to full scale CFD modeling, a hybrid method of vehicle underhood air flow and thermal analysis is presented in this paper, using the principle of flow network modeling (FNM) and CFD. In the present method, the entire flow domain in underhood is broken into various air flow passages, which are represented in a FNM model by nodes and links. For each individual air flow passage selected, CFD analysis is carried out to obtain the pressure drop (ΔP) vs. flow rate (Q) relation by considering various air flow rates, leading to a characteristic curve for each passage. The distribution of flow rates and pressure is then determined by FNM through solving 1D mass and momentum conservation equations over the entire flow network.

Idealized mathematical models, also known as lumped parameter models (LPMs), are widely used in analyzing vehicles for ride comfort and driving attributes. However, the limitations of some of these LPMs are sometimes not apparent and a rigorous comparative study of common LPMs is necessary in ascertaining their suitability for various dynamic situations. In the present study, the mathematical descriptions of three common LPMs, viz. quarter, half and full car models, are systematically presented and solved for the appropriate response parameters such as body acceleration, body displacement, and, pitch and roll angles using representative passive suspension system properties. By carrying out a comparison of the three stated LPMs for hump-type road profiles, important quantitative insights, not previously reported in the literature, are generated into their behaviors so that their applications can be judicious and efficient.

Taking full advantage of available traffic environment information, making control decisions, and then planning trajectory systematically under structured roads conditions is a critical part of intelligent vehicle. In this article, a lane-changing decision-making method for intelligent vehicle is proposed based on acceleration field. Firstly, an acceleration field related to relative velocity and relative distance was built based on the analysis of braking process, and acceleration was taken as an indicator of safety evaluation. Then, a lane-changing decision method was set up with acceleration field while considering driver’s habits, traffic efficiency and safety. Furthermore, velocity regulation was also introduced in the lane-changing decision method to make it more flexible.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

A quasi-dimensional multi-zone model for diesel spray combustion has been developed. The model contains most of the physical processes of diesel spray combustion, and is simplified and economical. The zone formation is based on the fuel injection parameters. For the wall jet penetration velocity, a new equation is used based on the effect of the impinging free jet on the wall jet. For the fuel evaporation, an approximate solution of the instantaneous variations of droplet diameter is given in the simple algebraic equations based on the individual effect of the evaporation and the heat transfer from ambient gas. The soot emission sub-model calculates the soot concentration. This model has been applied for a direct injection diesel engine. The calculated results have shown a reasonable agreement with the experimental results. A parametric study has been carried out.

Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors.

Forecasting the motion of the leading vehicle is a critical task for connected autonomous vehicles as it provides an efficient way to model the leading-following vehicle behavior and analyze the interactions. In this study, a personalized time-series modeling approach for leading vehicle trajectory prediction considering different driving styles is proposed. The method enables a precise, personalized trajectory prediction for leading vehicles with limited inter-vehicle communication signals, such as vehicle speed, acceleration, space headway, and time headway of the front vehicles. Based on the learning nature of human beings that a human always tries to solve problems based on grouping and similar experience, three different driving styles are first recognized based on an unsupervised clustering with a Gaussian Mixture Model (GMM).

Velocity prediction on hilly road can be applied to the energy-saving predictive control of intelligent vehicles. However, the existing methods do not deeply analyze the difference and diversity of road slope driving characteristics, which affects prediction performance of some prediction method. To further improve the prediction performance on road slope, and different road slope driving features are fully exploited and integrated with the common prediction method. A rolling prediction-based multi-scale fusion prediction considering road slope transition driving characteristics is proposed in this study. Amounts of driving data in hilly sections were collected by the advanced technology and equipment. The Markov chain model was used to construct the velocity and acceleration joint state transition characteristics under each road slope transition pair, which expresses the obvious driving difference characteristics when the road slope changes.

Significant A/F ratio excursion may occur during some engine transient operations, especially for transient periods of throttle tip in or tip out. A/F ratio excursion results in excessive emissions, extra fuel consumption, driveability deterioration and three-way-catalyst (TWC) efficiency drop. Simple two-parameter (X, τ) wall wetting models have traditionally been used to describe this transient A/F ratio excursion phenomenon. The transient fuel control techniques are utilized for this model to be applicable across vehicles, engines, fuel types and ambient conditions, so as to compensate for the A/F ratio excursion with the extra compensation fuel. More complicated model structures must be further expanded and model dependence on various environment conditions must be established to achieve a precise model. In this paper, a simple linear approach is proposed for transient fuel control, using least squares estimation.

This paper presents a study of LPG lean burn in a motorcycle SI engine. The lean burn limits are compared by several ways. The relations of lean burn limit with the parameters, such as engine speed, compression ratio and advanced spark ignition etc. are tested. The experimental results show that larger throttle opening, lower engine speed, earlier spark ignition timing, larger electrode gap and higher compression ratio will extend the lean burn limit of LPG. The emission of a LPG engine, especially on NOx emission, can be significantly reduced by means of the lean burn technology.

Internal combustion engines, as the dominant power source in the transportation sector and the primary contributor to carbon emissions, face both significant challenges and opportunities in the context of achieving carbon neutral goal. Biofuels, such as biodiesel produced from biomass, and zero-carbon fuel ammonia, can serve as alternative fuels for achieving cleaner combustion in internal combustion engines. The dual-fuel combustion of ammonia-biodiesel not only effectively reduces carbon emissions but also exhibits promising combustion performance, offering a favorable avenue for future applications. However, challenges arise in the form of unburned ammonia (NH3) and N2O emissions. This study, based on a ammonia-biodiesel duel-fuel engine modified from a heavy-duty diesel engine, delves into the impact of adjustments in the two-stage injection strategy on the combustion and emission characteristics.

High-speed video of combustion processes and cylinder pressure traces were obtained from a single-cylinder optical-accessible engine with a production four-valve cylinder head to study the mixture formation and flame propagation characteristics at near-stoichiometric start condition. Laser-sheet Mie-scattering images were collected for liquid droplet distributions inside the cylinder to correlate the mixture formation process with the combustion results. A dual-stream (DS) injector and a quad-stream (QS) injector were used to study the spray dispersion effect on engine starting, under different injection timings, throttle valve positions, engine speeds, and intake temperatures. It was found that most of the fuel under open-valve injection (OVI) conditions entered the cylinder as droplet mist. A significant part of the fuel droplets hit the far end of the cylinder wall at the exhaust-valve side.

This oil category was driven by two new cooled exhaust gas recirculation (EGR) engine tests operating with 15% EGR, with used oil soot levels at the end of the test ranging from 6 to 9%. These tests are the Mack T-10 and Cummins M11 EGR, which address ring, cylinder liner, bearing, and valve train wear; filter plugging, and sludge. In addition to these two new EGR tests, there is a Caterpillar single-cylinder test without EGR which measures piston deposits and oil consumption control using an articulated piston. This test is called the Caterpillar 1R and is included in the existing Global DHD-1 specification. In total, the API CI-4 category includes eight fired-engine tests and seven bench tests covering all the engine oil parameters. The new bench tests include a seal compatibility test for fresh oils and a low temperature pumpability test for used oils containing 5% soot. This paper provides a review of the all the tests, matrix results, and limits for this new oil category.

With the development of intelligent and electric vehicles, higher requirements are put forward for the active braking and regenerative braking ability of the braking system. The traditional braking system equipped with vacuum booster has difficulty meeting the demand, therefore it has gradually been replaced by the integrated braking system. In this paper, a novel Integrated Braking System (IBS) is presented, which mainly contains a pedal feel simulator, a permanent magnet synchronous motor (PMSM), a series of transmission mechanisms, and the hydraulic control unit. As an integrative system of mechanics-electronics-hydraulics, the IBS has complex nonlinear characteristics, which challenge the accurate pressure control. Furthermore, it is a completely decoupled braking system, the pedal force doesn’t participate in pressure-building, so it is necessary to precisely identify driver’s braking intention.

The Electronic Stability Program (ESP), as a key actuator of traditional automobile braking system, plays an important role in the development of intelligent vehicles by accurately controlling the pressure of wheels. However, the ESP is a highly nonlinear controlled object due to the changing of the working temperature, humidity, and hydraulic load. In this paper, an accurate pressure control strategy of single wheel during active braking of ESP is proposed, which doesn’t rely on the specific parameters of the hydraulic system and ESP. First, the structure and working principle of ESP have been introduced. Then, we discuss the possibility of Pulse Width Modulation (PWM) control based on the mathematical model of the high-speed switching valve. Subsequently, the pressure building characteristics of the inlet and outlet valves are analyzed by the hardware in the Loop (HiL) experimental platform.

This paper has designed a real time control algorithm to use ISG motor actively compensate the torque ripple produced by the engine, to reduce torsional vibration. This paper consists of 3 parts. In the first section, this paper has introduced the research object and its modification for experiments. Then the development of control strategy is presented. The engine dynamic model is built, and real-time control with a feedforward unit and a feedback unit is derived. Encoder and cylinder pressure is used for engine torque estimator. Then the ISG motor output the counter-waveform to make the overall output smooth. In order to verify the effectiveness of the control strategy, the final section has established a test bench, where two experiments are carried out. One of the experimental conditions is to set the engine at a constant operating point, while the other is to crank the engine from 0 rpm to idle speed with ISG motor.

The objective of this work is to develop a strategy to reduce the penalties in the diesel engine performance, fuel economy and HC and CO emissions, associated with the operation in the low temperature combustion regime. Experiments were conducted on a research high speed, single cylinder, 4-valve, small-bore direct injection diesel engine equipped with a common rail injection system under simulated turbocharged conditions, at IMEP = 3 bar and engine speed = 1500 rpm. EGR rates were varied over a wide range to cover engine operation from the conventional to the LTC regime, up to the misfiring point. The injection pressure was varied from 600 bar to 1200 bar. Injection timing was adjusted to cover three different LPPCs (Location of the Peak rate of heat release due to the Premixed Combustion fraction) at 10.5° aTDC, 5 aTDC and 2 aTDC. The swirl ratio was varied from 1.44 to 7.12. Four steps are taken to move from LTC to ALTC.

The objective of the research into modeling and simulation was to provide an improvement to the Wayne State EcoCAR 2 team’s math-based modeling and simulation tools for hybrid electric vehicle powertrain analysis, with a goal of improving the simulation results to be less than 10% error to experimental data. The team used the modeling and simulation tools for evaluating different outcomes based on hybrid powertrain architecture changes (hardware), and controls code development and testing (software). The first step was model validation to experimental data, as the plant models had not yet been validated. This paper includes the results of the team’s work in the U.S. Department of Energy’s EcoCAR 2 Advanced vehicle Technical Competition for university student teams to create and test a plug-in hybrid electric vehicle for reducing petroleum oil consumption, pollutant emissions, and Green House Gas (GHG) emissions.

The adoption of lithium-ion batteries in vehicle electrification is fast growing due to high power and energy demand on hybrid and electric vehicles. However, the battery overall performance changes with time through the vehicle life. This paper investigates the electric vehicle battery cell aging under different usages. Battery cell experimental data including open circuit voltage and internal resistance is utilized to build a typical electric vehicle model in the AVL-Cruise platform. Four driving cycles (WLTP, UDDS, HWFET, and US06) with different ambient temperatures are simulated to acquire the battery cell terminal currents. These battery cell terminal current data are inputs to the MATLAB/Simulink battery aging model. Simulation results show that battery degrades quickly in high ambient temperatures. After 15,000 hours usage in 50 degrees Celsius ambient temperature, the usable cell capacity is reduced up to 25%.