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Upcoming, increasingly stringent greenhouse gas (GHG) as well as emission limits demand for powertrain electrification throughout all vehicle applications. Increasing complexity of electrified powertrain architectures require an overall system approach combining modular component technology with integration and industrialization requirements when heading for further significant efficiency optimization. At the same time focus on reduced development time, product cost and minimized additional investment demand reuse of current production, machining, and assembly facilities as far as possible. Up to date additive manufacturing (AM) is an established prototype component, as well as tooling technology in the powertrain development process, accelerating procurement time and cost, as well as allowing to validate a significantly increased number of variants. The production applications of optimized, dedicated AM-based component design however are still limited.

The author has developed UV based photocatalytic air purification system (Mathur, 2021, 2122, 2023) that can eliminate all pathogens from the cabin air including COVID-19. In this study, the focus is to determine the risk of infection due to pathogens/germs in the cabin of an automobile. Author has determined the risk of infection by using Wells-Riley model and conducted CFD analysis to determine propagation of virus in cabin as a function of: 1 Cabin Volume & Number of Occupants (Wells-Riley Model in OSA mode): (i) Cabin volume from: Small Sedan, Large Sedan and a SUV; with 4 occupants (males & females); Number of infector 1; Air flowrate (m3/min); (ii) A 15-seater minibus – with 10 occupants (males); Number of infectors 1 & 2; Air flowrate (m3/min) 2 CFD to simulate 4 occupants and 1 infector in an automotive cabin – Current investigation is for talking, coughing and sneezing with blower off in Recirc mode wit (i) Infector in the front seat; (ii) Infector in the rear seat.

Fiber reinforced additive manufacturing (FRAM) is a fused deposition modelling (FDM) additive manufacturing (AM) process which produces composite print layers - polymer matrix and reinforcing fiber. This work proposes a novel method which utilizes FRAM design freedom and simultaneously optimizes 3D print orientation and component topology to improve the response of a mass minimization problem statement. The method is robust and is designed to solve industry-applicable problem statements (mass minimization) with complex geometry and loading. Design sensitivities of 3D print orientation design variables, (θ1, θ2, θ3), are calculated using finite differencing and gradient descent is used to converge to an optimized print orientation. Changing 3D print orientation alters anisotropic material properties to improve the structural response of the component in the prescribed load-cases.

The next generation of digital cockpits requires modern architectures to be successful and affordable. This paper provides an in-depth view on the future of digital cockpit architectures. The currently emerging architectures are explored with two main points in focus: The key experiences that drive customer expectations and the options to cost-effectively meet those expectations—while keeping the vehicle affordable. Modern architectures rely on middleware services. Well-designed middleware services allow for an efficient and reusable approach across different model lines and market segments. The paper presents this approach. The new architectures also lead to a transformation of the partner ecosystem between original equipment manufacturers (OEMs) and component suppliers. OEMs try to lever this system while maintaining control over their offerings. These changes transform the traditional semiconductor industry as a whole.

The functions of modern intelligent connected vehicles are becoming increasingly complex and diverse, and software plays an important role in these advanced features. In order to decouple the software and the hardware and improve the portability and reusability of code, Service-Oriented Architecture (SOA) has been introduced into the automotive industry. Data Distribution Service (DDS) is a widely used communication middleware which provides APIs for service-oriented Remote Procedure Call (RPC) and Service-Oriented Communications (SOC). By using DDS, application developers can flexibly define the data format according to their needs and transfer them more conveniently by publishing and subscribing to the corresponding topic. However, current open source DDS protocols all use unicast communication during the transmission of user data. When there are multiple data readers subscribing to the same topic, the data writer needs to send a unicast message to each data reader individually.

To enhance the transient vibration performance of the vehicle at key on and key off, a method for optimizing mount parameters of a powertrain mounting system (PMS) is proposed. Uncertainties of mount parameters widely exist in a PMS, so a method for optimizing mount parameters of a PMS, which treats the mount parameters of a PMS as uncertain, is also proposed in this paper. Firstly, a 13 degrees of freedom (DOFs) model including car body with 3 DOFs, a PMS with 6 DOFs and unsprung mass with 4 DOFs is established, and the acceleration of the active side of mounts is calculated. An experiment is carried out to measure the accelerations located at active and passive sides of each mount and the accelerations of seat track. A comparison is made between the measured and estimated accelerations, and the proposed model is validated. Two optimization methods for the PMS are proposed based on the developed 13 DOFs model.

Autonomous driving technology has advanced significantly in recent years, thanks to the innovations in vehicle design and artificial intelligence. This technology provides a more convenient and comfortable driving experience for both drivers and passengers. However, current autonomous driving systems still face some difficulties, such as the need for human intervention in critical situations. Switching control from the system to the driver without assessing their alertness or health status could pose a risk. Therefore, autonomous driving systems should be able to monitor and evaluate the driver's condition before handing over the control. This paper thus proposes an in-cabin detection system that monitors driver status using a camera. The system consists of software modules that use deep learning techniques to analyze the input from an IR camera.

In-cylinder pressure measurement is an important tool in internal combustion engine research and development for combustion, cycle performance, and knock analysis in spark-ignition engines. In a typical laboratory setup, a sub crank angle resolved (typically between 0.1o and 0.5o) optical encoder is installed on the engine crankshaft, and a piezoelectric pressure transducer is installed in the engine cylinder. The charge signal produced by the transducer due to changes in cylinder pressure during the engine cycle is converted to voltage by a charge amplifier, and this analog voltage is read by a high-speed data acquisition (DAQ) system at each encoder trigger pulse. The high speed of engine operation and the need to collect hundreds of engine cycles for appropriate cycle-averaging requires significant processor speed and memory, making typical data acquisition systems very expensive.

Understanding driving behavior is crucial for enhancing traffic safety. While previous studies have primarily explored driving behavior using either statistical or machine learning methods, comprehensive assessments employing both methods under various driving mode are limited. In this study, we employ both machine learning and statistical approaches to model driving behavior. First, we design a comprehensive driver grading system to assess the behavior of drivers under different driving modes. Additionally, we present an extended isolation forest-based model to classify driving behavior using data without labels, saving time and effort. Results illustrate that safe driving is more consistent and stable, while aggressive driving exhibits more intensive changes. They also demonstrate that drivers can exhibit various behaviors under different modes, serving as a benchmark for further driver modeling.

This study assessed a driver’s ability to safely manage Super Cruise lane changes, both driver commanded (Lane Change on Demand, LCoD) and system triggered Automatic Lane Changes (ALC). Data was gathered under naturalistic conditions on public roads in the Washington, D.C. area with 12 drivers each of whom were provided with a Super Cruise equipped study vehicle over a 10-day exposure period. Drivers were shown how to operate Super Cruise (e.g., system displays, how to activate and disengage, etc.) and provided opportunities to initiate and experience commanded lane changes (LCoD), including how to override the system. Overall, drivers experienced 698 attempted Super Cruise lane changes, 510 Automatic and 188 commanded LCoD lane changes with drivers experiencing an average of 43 Automatic lane changes and 16 LCoD lane changes.

In this study, an optimized structure for opening the headlining considering the deployment of the face-to-face roof airbag was studied. It was confirmed that the deployment performance differs depending on the skin of the headlining, and a standardized structure with mass production was proposed. Non-woven fabric and Tricot skin, which are economical and high-end specifications, satisfy the performance of PVC fusion application specifications after cutting 80% of the skin. The structure that satisfies the entire body including the knit specifications is a type that separates the roof airbag area piece, the corresponding soft piece is separated, and the deployment performance is satisfied with safety. Therefore, the structure is proposed as a standardized structure. This structure is expected to be applicable to roof DAB (Driver Airbag), PAB (Passenger Airbag), and Sunroof Airbag, which will be necessary technologies to secure indoor space.

The hybrid system's thermal strategy is centered around controlling the cooling of the motor, inverter, DCDC and evaporator. In this electric drive circuit system, the water temperature sensor is positioned at the radiator outlet rather than within it. Consequently, when determining the required air volume for radiator cooling and water demand for sub-components of the electric drive circuit, an estimation of the inlet water temperature becomes necessary. This estimation relies on a heat transfer formula that converts heat released by circuit sub-components into their contribution to temperature rise within the circuit plus the outlet temperature from the previous round through the radiator to determine inlet water temperature. The inverter's heat transfer power depends on voltage and current levels. Adjusting motor torque leads to rapid changes in current flow while maintaining a low speed for optimal flow rate through the electric drive pump.

The existing FCEV have been developed with only a few vehicle models. With the diversification of both passenger and commercial FCEV lineups, as well as the increasing demand for vehicle trailer towing, there is a growing need for high-capacity fuel cell stacks to be applied in vehicles. However, at the current level, there are limitations and issues that arise, such as insufficient power output and reduced driving speed. As a results, the importance of thermal energy management has been increasing along with the increase in required power. Traditional cooling performance enhancement methods have mainly focused on developing increased hardware specifications, but even this approach has reached its limitation due to package, cost and weight problem. Therefore, it is essential to develop a new cooling system to solve the increases in heat dissipation.

The inverter of the electrical driven compressor (EDC) is subjected to high thermal loads which are resulting from external temperature exposure and from compressor solicitations from the vehicle thermal loop (refrigerant nature, flow rate, compression rate, initial temperature). An incorrect thermal management of the inverter might lead to a significant decrease of efficiency which degrades the performance, product lifetime (electronics components failure) and even worse, might lead to a hazardous thermal event (HTE). The need of the automotive market to drastically decrease project development time, requires decreasing design and simulation activities lead time without degrading the design robustness, which is one additional complexity and challenge for the R&D team.

A set of enthalpy difference test equipment is set up to test flow and heat exchange performance of chillers. The empirical correlations for the convective heat transfer coefficients on the coolant side and the refrigerant side are obtained by fitting the test data, and a two-particle lumped parameter model of the chiller is established. Based on this, the heat exchange performance of the chiller under different operating conditions is given. The effects of herringbone corrugated plate parameters, including angle, pitch, and depth, on flow and heat exchange performance of chillers under different flow rates are further studied. Using the Wilson plot method in test design, the thermal resistance of convective heat transfer on each side is separated from the total thermal resistance to calculate the convective heat transfer coefficient.

The need for even more efficient internal combustion engines in the road transportation sector is a mandatory step to reduce the related CO2 emissions. In fact, this sector impacts significantly on greenhouse gases worldwide, and the path toward hybrid and electric powertrains has just begun. In particular, in heavy-duty vehicles the full electrification of the powertrain is far to be considered as a really feasible alternative. So, internal combustion engines will still play a significant role in the near/medium future. Hence, technologies having a low cost to benefits (CO2 reduction) ratio will be favorably introduced in existing engines. Thermal management of engines is today a recognized area of research. Inside this area, the interest toward the lubricant oil has a great potential but not yet fully exploited. Engine oil is responsible of the mechanical efficiency of the engine which has a significant potential of improvement.

Rotor-only ducted low-pressure axial fans play a crucial role in automotive thermal management of the tightly packed under-hood region. Most current scientific work concerning low-pressure axial fans investigate the aerodynamic performance of these fans while operating with uniform inlet flow conditions. This is rarely the case in real-world applications. This work aims to investigate the aerodynamic performance of low-pressure axial fans operating with upstream blockages. First, a validation study is performed in the absence of any upstream blockage. Numerical results are compared against publicly available experimental data. Steady-state, Reynolds-Averaged Navier Stokes (RANS) analysis is performed on a single-blade passage. The validation study also evaluates the choice of turbulence model and suggests the use of the k- ε turbulence model with wall functions for the best comparison against experimental data.

Based on the basic structure and operation function of engine throttle, according to the actual structure of a throttle, a 3-dimensional simulation of the transient airflow during the rotation of the throttle from the closed position to the fully open position is realized by using CFD together with the moving mesh technology and the user-defined program. The influence of the throttle movement on the airflow process is studied. The velocity field, pressure field, and flow noise field are analyzed at different angles of throttle rotation. The numerical simulation results show that at the beginning period of the throttle rotation, the vortex appears in the flow field behind the throttle, and the drop of the air pressure between the upstream and downstream position of the throttle is sharp.

Lubrication systems play a major role not only in the durability of modern IC engines but also in performance and emissions. The design of the lubrication system influences the brake thermal efficiency of the engine. Also, efficient lubrication reduces the engine's CO2 emissions significantly. Thus, it is critical for an IC engine to have a well-designed lubrication system that performs efficiently at all engine operating conditions. The conventional lubrication system has a fixed-displacement oil pump that can cater to a particular speed range. However, a fully variable displacement oil pump can cater to a wide range of speeds, thereby enhancing the engine fuel efficiency as the oil flow rates can be controlled precisely based on the engine speed and load conditions. This paper primarily discusses the optimization of a lubrication system with a Variable Displacement Oil Pump (VDOP) and a map-controlled Piston Cooling Jet (PCJ) for a passenger car diesel engine.

Recently, the environmental temperature of vehicles is changing due to the electrification of vehicles and improved internal combustion engine system to reduce carbon emissions. However, mechanical properties of plastic materials change very sensitively to environmental temperature changes, and mechanical properties decrease when exposed to high temperatures. Therefore, it is important to estimate lifespan estimation of plastic parts according to temperature changes. In this paper, reliability analysis process to estimate the maximum service temperature of plastic parts was developed using aging data of material properties, environmental condition data of automotive parts, and field driving condition data. Changes in the mechanical properties of plastic materials such as glass fiber reinforced polyamide materials were tested. The environmental exposure temperature of the vehicle and parts was measured, and the general driving pattern of the vehicle was analyzed.