The increasing awareness on the harmful effects on the environment of traditional Internal Combustion Engines (ICE) is driving the industry toward cleaner powertrain technologies such as battery-driven Electric Vehicles. Nonetheless, the high energy density of Li-Ion batteries can cause strong exothermic reactions under certain conditions that can lead to catastrophic results, called Thermal Runaway (TR). Hence, a strong effort is being placed on understanding this phenomena and increase battery safety. Specifically, the vented gases and their ignition can cause the propagation of this phenomenon to adjancent batteries in a pack. In this work, Computational Fluid Dynamics (CFD) are employed to predict this venting process in a LG18650 cylindrical battery. The ejection of the generated gases was considered to analyze its dispersion in the surrounding volume through a Reynolds-Averaged Navier-Stokes (RANS) approach.
This work puts forward an original autonomous planning and control framework addressing inherent modeling complexity limit through efficient heterosis between latency-connective graph estimation and generative exploration with an aim to enhance trajectory quality and resiliency in unpredicted conditions. The holistic approach encompasses state and cost prediction facilitated via morphable signature mechanism utilizing anti-cloak characteristics derived from environmental graph. In principle, a dynamic graph neural network is proposed with regards to adaptively capture essential influence caused by interactive agents and reciprocal belief augmentation. Moreover, high efficiency exploration is concerted with signature-enhanced prediction system for non-ideal perception conditions. The exploration scheme takes advantage of confidence optimization function to generate trajectory refinement over non-conventional operating circumstances.
Churning loss is an important energy loss term for rolling bearings at high speed condition. However, it is quite challenging to accurately calculate the churning loss. A CFD study based on unsteady Reynolds-Averaged-Navier-Stokes that resolves the gas-liquid interface was performed to examine the unsteady multiphase flow in a roller/ball bearing. In this study, the rotating motion of the cage, races, rollers/balls about the shaft as well as self-rotation of rollers/balls about their own axis were accounted to accurately predict the oil distribution in various parts of the bearings. A novel meshing strategy is presented to resolve thin gaps between the roller/balls and the races/cage while preserving the shape of balls/rollers, races and cage. Seven and five rotational speeds of the shaft have been examined for roller bearing and ball bearing respectively.
In the field of automotive aerodynamics, there's a consistent need for tools that effectively manage both rapid design changes and comprehensive simulations. The recent GPU code update to the PowerFLOW, Lattice Boltzmann simulation tool is an attempt to meet this need. An important feature of this update is the inclusion of the Sliding Mesh rotating reference frame, which improves rim modeling accuracy. This modification provides a clearer depiction of vehicle aerodynamics, aiming for balanced and efficient designs. The updated GPU solver has been tested with two main resolutions. First, a low-resolution aerodynamics scheme which can assist designers and stylists in their initial stages of design. This setup aims to offer a rapid iterative design process. In addition, for more detailed analysis, full-scale resolution simulation setups are possible with the NVIDIA A100's 80GB memory capacity.
The adoption of Electric Vehicles (EVs) is primarily limited by their dependence on batteries, which have lesser power density as compared to conventional fossil fuels as well as its ageing deterioration issues over time. Therefore, there is an urgent need to understand the modifications in battery performance characteristics with respect to changes in temperature, charging behaviour and usage pattern, low and high charge states, current variations etc. To resolve such issues, this work proposes the development of a battery digital twin model to accurately reflect battery dynamics during run time. A digital twin is a virtual model replicating a physical system's characteristics. The digital twin is developed using a physics and machine learning model trained with bench-level and vehicle level actual test data. It uses an equivalent circuit model (ECM) to predict the battery's internal resistance and polarization effect due to ionic diffusion process in the cell.
The proliferation of electric vehicles (EVs) is making big transition in the automotive industry, promising reduced greenhouse gas emissions and improved energy efficiency. The architectural configurations and power distribution strategies necessitate the optimization of their drivability performance, all-electric ranges, and overall efficiency. This paper reports the efforts of the University of California at Riverside (UCR) EcoCAR team in EV architecture selection to match the EcoCAR EV Challenge theme of shared mobility for disadvantaged communities. The UCR EcoCAR team conducted a comprehensive analysis of various EV architectures (including rear-wheel drive, front-wheel drive, and all-wheel drive) and motor parameters, considering a spectrum of targeted vehicle technology specifications such as acceleration and braking performance, fuel economy, and cargo/passenger capacity.
In this paper, water droplet dynamics in FC channels were investigated by applying numerical and experimental methodologies. Specifically, digital imaging with high-spatial resolution was applied for characterising the micro-channel surface and defining the texture of the Gas Diffusion Layer (GDL) of a Membrane electrode assembly (MEA). The optical results allowed the definition of a 3D geometry of the GDL to use in CFD simulations. Moreover, a custom procedure of image processing permitted the estimation of the contact angles of droplets deposited on the GDL (123°) and channel walls (50°-60°) for a wide range of droplet size (0.3-1.2mm). The determined specifications were used as boundary conditions for a 3D CFD two phase simulation employing the Volume of Fluid (VOF) model. Droplets were initialized on the walls and their dynamics were studied under increasing air flow, up to 20 m/s.
This study experimentally investigates the combustion stability in RCCI engines along with the gaseous (regulated and unregulated) and particle emissions. Multifractal analysis is used to characterize the cyclic combustion variations in the combustion parameters (such as IMEP, CA50, Pmax) of the RCCI engine. The investigation is carried out on a modified single-cylinder diesel engine to operate in RCCI combustion mode. The RCCI combustion mode is tested for different fuel premixing ratio (r_p) and diesel injection timing (SOI) at fixed engine speed (1500rpm) and load (1.5 bar BMEP). The particle number characteristics and gaseous emissions are measured using a differential mobility spectrometer (DMS500) and Fourier Transform Infrared Spectroscopy (FTIR) along with Flame Ionizing Detector (FID), respectively. The results indicate that the NOx emissions decrease with advanced SOI while the methane (CH4) emission increases.
To mitigate the NOx emissions from diesel engines, the adoption of exhaust gas recirculation (EGR) has gained widespread acceptance as a technology. Nonetheless, employing EGR has the drawback of elevating soot emissions. The use of hydrogen-enriched air with EGR in a diesel engine (dual-fuel operation), offers the potential to decrease in-cylinder soot formation while simultaneously reducing NOx emissions. The present study numerically investigates the effect of hydrogen energy share and engine load on the formation and emission of soot and NOx emission from hydrogen-diesel dual-fuel engine. The numerical investigation is performed using an n-heptane/H2 reduced reaction mechanism with a two-step soot model in ANSYS FORTE. To enhance the accuracy of predicting dual-fuel combustion in a hydrogen-diesel dual-fuel engine, a reduced n-heptane reaction mechanism is integrated with a hydrogen reaction mechanism using CHEMKIN.
Ammonia (NH3), a zero-carbon fuel, has great potential for internal combustion engine development. However, its high ignition energy, low laminar burning velocity, a narrow range of flammability limits, and high latent heat of vaporization are not conducive for engine application. This paper numerically investigates the feasibility of utilizing ammonia in a heavy-duty diesel engine, specifically through the method of low-pressure direct injection (LP-DI) of hydrogen to ignite ammonia combustion. The study compares the engine's combustion and emission performance by optimizing four critical parameters: excess air ratio, hydrogen blending ratio, ignition timing, and hydrogen injection timing. The results reveal that excessively high hydrogen blending ratios lead to an advanced combustion phase, resulting in a reduction in indicated thermal efficiency.
Since Non-Road Mobile Machinery (NRMM) China stage IV legislation has been implemented from 2023, some engines within maximum rated power between 37 to 560 kW are required for gaseous emissions, particulate matter(PM) and particulate number (PN) limitation, evaluated over testing cycle of Non-Road Transient Cycle (NRTC) and Non-Road Steady Cycle (NRSC). The pollutants from diesel engines, widely used in NRMM applications, can be controlled using aftertreatment systems which are comprise of a diesel oxidation catalyst (DOC) and a diesel particulate filter (DPF), or optionally a selective catalytic reduction (SCR). In this presentation, a compact D-DPF design is introduced and discussed on application in harvesters, tractors, and forklifts. Because harvesters have higher exhaust gas temperature than other applications, more passive regeneration behaviors were occurred during working conditions.
Simulators are essential part of the development process of vehicles and their advanced functionalities. The combination of virtual simulator and Hardware-in-the-loop technology accelerates the integration and functional validation of ECUs and mechanical components. In this study, a real-time capable tire model has been developed and coupled with an innovative simulation apparatus. On-track tests were executed to collect data necessary for tire modelling using an experimental vehicle equipped with wheel force transducer, to measure force and moments acting on tire contact patch. The steering wheel was instrumented with a torque sensor, while tie-rod axial forces were quantified using loadcells. The simulation apparatus is composed of a static and a dynamic simulator. The static simulator integrates the entire steering system from the steering column up to tie rods. Tie-rods dynamic forces are applied by two torque motors.
The EPB(Electric Parking Brake) system is divided into two parts based on VDA305-100 recommendation. One part of the EPB system contains the parking brake actuator, caliper and actuation logic (parking brake controller, PBC). The second part of the EPB system is called to the HOST which contains the EPB power electronics, necessary peripherals and controls the functions that the driver can experience. According to the VDA recommendation, the PBC is responsible for recognition of a fault in the parking brake actuator based on the measured values transmitted from HOST such as EPB motor voltage and current. Due to mechanical fault injection limitations, failsafe tests require physically electrical emulation caused by parking brake actuator faults to verify the parking brake actuator fault detection and management algorithm.
In order to study the effects of different factors on the static and dynamic characteristics of air springs, three models were established to calculate the static and dynamic characteristics of air springs, including modeling at the design position,modeling only considering the straight state,and modeling considering the thickness of the bellows in the straight state. Static stiffness of air springs is calculated using three different models and are compared with experiments. In the straight state model considering the thickness of the bellow, the influence of aluminum tube and bellows thickness on the static stiffness are considered, and the modeling with the straight state solved the problem of the change in cord angle after the air spring was inflated and expanded. The established model is then used to calculate static and dynamic characteristics of air springs, such as static stiffness, hysteresis loop, and dynamic stiffness.
Electro-Mechanical Brake (EMB) system, which has the advantages of no liquid medium, fast braking response and complete decoupling, etc., could meet the functional requirements of autonomous vehicle such as high-quality active braking and high-intensity regenerative braking. Therefore, the EMB is considered to be one of the ideal carriers of future vehicle chassis. However, when the EMB receives time-varying braking requirements in different working conditions, the traditional clamping force control strategy with fixed control parameters is difficult to maintain high-quality braking performance. At the same time, the nonlinear friction resistance between transmission mechanisms also affects the accuracy of clamping force controller. This paper presents an adaptive clamping force control strategy for EMB considering nonlinear frictional resistance.
A time domain analysis method of ride comfort and energy dissipation characteristics is proposed for automotive vibration PID control. A two degree of freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined. The PID control parameters were tuned using the differential evolution algorithm, and to improve the algorithm's adaptive ability, an adaptive operator was introduced in this article, so that the mutation factor of the differential evolution algorithm can change with the number of iterations. Based on PID control and its parameter tuning, a time-domain solution method for two types of vibration response varaibles, their root mean square values and the average power of energy consumption vibration of automotive vibration PID control is proposed.
Semi-active suspension system (SASS) could enhance the ride comfort of the vehicle across different operating conditions through adjusting damping characteristics. However, current SASS are often calibrated based on engineering experience when selecting parameters for its controller, which complicates the achievement of optimal performance and leads to a decline in ride comfort for the vehicle being controlled. Linear quadratic constrained optimal control is a crucial tool for enhancing the performance of semi-active suspensions. It considers various performance objectives, such as ride comfort, handling stability, and driving safety. This study presents a control strategy for determining optimal damping force in SASS to enhance driving comfort. First, we analyze the working principle of the SASS and construct a seven-degree-of-freedom model.
The electrochemical pseudo-two dimensional (P2D) model is one of the most promising approaches that provide suitable physical depth at reasonable computational costs for the simulation of lithium-ion batteries. The parameterization of the P2D model plays an important role as it decides about the acceptance and application range of subsequent simulation studies. Electrical impedance spectroscopy (EIS) is commonly applied to characterize the batteries and to obtain the exchange current density and the electrode diffusion coefficient of a given electrode material. EIS measurements performed with frequencies ranging from 1 MHz down to 10mHz typically do not cover clearly isolated solid state diffusion processes of lithium-ions in positive or negative electrode materials. To extend the frequency range down to 10µHz, the distribution relaxation times (DRT) is a sound analysis method.