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The rise of Software-Defined Vehicles (SDV) has rapidly advanced the development of Advanced Driver Assistance Systems (ADAS), Autonomous Vehicle (AV), and Battery Electric Vehicle (BEV) technology. While AVs need power to compute data from perception to controls, BEVs need the efficiency to optimize their electric driving range and stand out compared to traditional Internal Combustion Engine (ICE) vehicles. AVs possess certain shortcomings in the current world, but SAE Level 2+ (L2+) Automated Vehicles are the focus of all major Original Equipment Manufacturers (OEMs). The most common form of an SDV today is the amalgamation of AV and BEV technology on the same platform which is prominently available in most OEM’s lineups. As the compute and sensing architectures for L2+ automated vehicles lean towards a computationally expensive centralized design, it may hamper the most important purchasing factor of a BEV, the electric driving range.

Shell-and-tube heat exchangers, commonly referred to as radiators, are the most prevalent type of heat exchanger within the automotive industry. A pivotal goal for automotive designers is to increase their thermal effectiveness while mitigating pressure drop effects and minimizing the associated costs of design and operation. Their design is a lengthy and intricate process involving the manual creation and refinement of computer-aided design (CAD) models coupled with iterative multi-physics simulations. Consequently, there is a pressing demand for an integrated tool that can automate these discrete steps, yielding a significant enhancement in overall design efficiency. This work aims to introduce an innovative automation tool to streamline the design process, spanning from CAD model generation to identifying optimal design configurations. The proposed methodology is applied explicitly to the context of shell-and-tube heat exchangers, showcasing the tool's efficacy.

With the increasing demand for efficient & clean transport solutions, applications such as road transport vehicles, aerospace and marine are seeing a rise in electrification at a significant rate. Irrespective of industries, the main source of power that enables electrification in mobility applications like electric vehicles (EV), electric ships and electrical vertical take-off & landing (e-VTOL) is primarily a battery making it fundamentally a DC system. Fast charging solutions for EVs & e-VTOLs are also found to be DC in nature because of several advantages like ease of integration, higher efficiency, etc. Likewise, the key drivers of the electric grid are resulting in an energy transition towards renewable sources, that are also essentially DC in nature. Overall, these different business trends with their drivers appear to be converging towards DC power systems, making it pertinent.

The automotive industry has seen accelerating demand for electrified transportation. While the complexity of conventional ICE vehicles has increased, the powertrain still largely consists of a mechanical system. In contrast, vehicle architectures in electrified transportation are a complex integration of power electronics, batteries, control units, and software. This shift in system architecture impacts the entire organization during new product development, with increased focus on high power electronic components, energy management strategies, and complex algorithm development. Additionally, product development impact extends beyond the vehicle and impacts charging networks, electrical infrastructure, and communication protocols. The complex interaction between systems has a significant impact on vehicle safety, development timeline, scope, and cost.

Wet-sump transmissions are widely used in heavy duty and medium duty vehicles. As these transmissions do not have a dedicated forced lubrication system, it is important that the gear train, shafts, and enclosure are designed appropriately so that enough oil splashes to critical locations to ensure sufficient lubrication. The lubrication effectiveness of such transmissions can be studied through detailed tests or numerical simulations. Often, the vehicle, and therefore the transmission, encounters some severe operating conditions, such as climbing on an incline, driving downhill, etc. Studying these conditions through tests is an expensive process and this imposes the need for an analysis first approach. In this paper, the 3D multiphase Volume of Fluid (VOF) method is used to examine two such extreme cases: an 8-degree tilted installation of transmission in a vehicle, and an inclined condition of transmission during a 10-degree uphill climb.

Roots blower is a rotary positive displacement pump which operates by pumping a fluid with a pair of meshing lobes. Recent trends in automotive industry demands high power density solutions for various applications. In comparison with legacy applications, compressors for high power density applications demand continuous operation with harsher duty cycle as well as demand higher pressure ratios. Because of longer duty cycles, it will be subjected to high heat loads which will cause a rise in temperatures of timing gears, bearings, and other components within the assembly. Accurate prediction of thermal performance is critical to design a durable and efficient roots blower for high power density applications. Thermal analysis of an assembly of roots blower involves modelling of multi-physics phenomena. This paper details a coupled CFD analysis approach to predict temperatures of roots blower components and timing gear case oil. Timing gears are lubricated using wet sump lubrication.

The use of electrical contacts in aerospace applications is crucial, particularly in connectors that transmit signal and power. Crimping is a widely preferred method for joining electrical contacts, as it provides a durable connection and can be easily formed. This process involves applying mechanical load to the contact, inducing permanent deformation in the barrel and wire to create a reliable joint with sufficient wire retention force. This study utilizes commercially available Abaqus software to simulate the crimping process using an explicit solver. The methodology developed for this study correlates FEA and testing for critical quality parameters such as structural integrity, mechanical strength, and joint filling percentage. A four-indenter crimping tool CAD model is utilized to form the permanent joint at the barrel-wire contact interfaces, with displacement boundary conditions applied to the jaws of the tool in accordance with MIL-C-22520/1C standard.

The transmission is an integral part of the driveline in an automotive vehicle. Global vehicle pass-by noise regulations are becoming more stringent and transmissions are expected to be very quiet. Typically for an automotive system, engine is the most dominant noise source and transmissions have been considered a secondary noise source but as the trend is shifting towards more electric vehicles where engine noise is absent and overall vehicle is becoming quieter, the transmission can be more of a significant noise contributor. Gear whine is the major concern for sound radiation from the transmission. The gear whine simulation and acoustic radiation analysis of the transmission using traditional methods (FEM and BEM) is a crucial but very time-consuming part of the product development cycle. On top of that, electric vehicle transmissions operate at higher RPM which in turn increases the excitation frequency arising from the gear whine phenomenon.

In the past decades, automotive structure design has sought to minimize its mass while maintaining or improving structural performance. As such, topology optimization (TO) has become an increasingly popular tool during the conceptual design stage. While the designs produced by TO methods provide significant performance-to-mass ratio improvements, they require considerable computational resources when solving large-scale problems. An alternative for large-scale problems is to decompose the design domain into multiple scales that are coupled with homogenization. The problem can then be solved with hierarchical multiscale topology optimization (MSTO). The resulting optimal, homogenized macroscales are de-homogenized to obtain a high-fidelity, physically-realizable design. Even so MSTO methods are still computationally expensive due to the combined costs of solving nested optimization problems and performing de-homogenization.

Due to increased urgency regarding environmental concerns within the transportation industry, sustainable solutions for combating climate change are in high demand. One solution is a widespread transition from internal combustion engine vehicles (ICEVs) to battery electric vehicles (BEVs). To facilitate this transition, reliable energy consumption modeling is desired for providing quick, high-level estimations for a BEV without requiring extensive vehicle and computational resources. Therefore, the goal of this paper is to create a simple, yet reliable vehicle model, that can estimate the energy consumption of most electric vehicles on the market by using parameter normalization techniques. These vehicle parameters include the vehicle test weight and performance to obtain a unified net Willans line to describe the input/output power using a linear relationship.

Commercial vehicles require fast aftertreatment heat-up to move the SCR catalyst into the most efficient temperature range to meet upcoming NOX regulations while minimizing CO2. The focus of this paper is to identify the technology levers when used independently and also together for the purpose of NOX and CO2 reduction toward achieving 2027 emissions levels while remaining CO2 neutral or better. A series of independent levers including cylinder deactivation, LO-SCR, electric aftertreatment heating and fuel burner technologies were explored. All fell short for meeting the 2027 CARB transient emission targets when used independently. However, the combinations of two of these levers were shown to approach the goal of transient emissions with one configuration meeting the requirement. Finally, the combination of three independent levers were shown to achieve 40% margin for meeting 2027 transient NOx emissions while remaining CO2 neutral.

The pre-prototype development of a simulated rule-based hybrid energy management strategy for a 2019 Chevrolet Blazer RS converted parallel P4 full hybrid is presented. A vehicle simulation model is developed using component bench data and validated using EPA-reported dynamometer fuel economy test data. A combined Willans line model is proposed for the engine and transmission, with hybrid control rules based on efficiency-derived engine power thresholds. Algorithms are proposed for battery state of charge (SOC) management including engine loading and one pedal strategies, with battery SOC maintained within 20% to 80% safe limits and charge balanced behavior achieved. The simulated rule-based hybrid control strategy for the hybrid vehicle has an energy consumption reduction of 20% for the Hot 505, 3.6% for the HwFET, and 12% for the US06 compared to the stock vehicle.

The influence of driver modeling and drive cycle target speed trace modification on vehicle dynamics within energy consumption simulations is studied. EPA dynamometer speed error criteria and the SAE J2951 Drive Quality Evaluation for Chassis Dynamometer Testing standard are applied to simulation outputs as proposed components of simulation validation, providing guidelines for acceptable vehicle speed outputs and allowing comparison of simulation results to reported EPA dynamometer test statistics. The combined effect of driver model tuning and drive cycle interpolation methods is investigated for the UDDS, HwFET and US06 drive cycles, with EPA-specified linearly interpolated speed trace and a PI controller driver as a baseline result.

A new and unique electric vehicle powertrain model based on bidirectional power flow for propel and regenerative brake power capture is developed and applied to production battery electric vehicles. The model is based on a Willans line model to relate power input from the battery and power output to tractive effort, with one set of parameters (marginal efficiency and an offset loss) for the bidirectional power flow through the powertrain. An electric accessory load is included for the propel, brake and idle phases of vehicle operation. In addition, regenerative brake energy capture is limited with a regen fraction (where the balance goes to friction braking), a power limit, and a low-speed cutoff limit. The purpose of the model is to predict energy consumption and range using only tractive effort based on EPA published road load and test mass (test car list data) and vehicle powertrain parameters derived from EPA reported unadjusted UDDS and HWFET energy consumption.

Pedal misapplication (PM) crashes, i.e., crashes caused by a driver pressing one pedal while intending to press another pedal, have historically been identified by searching unstructured crash narratives for keywords and verified via labor-intensive manual inspection. This study proposes an alternative method to identify PM crashes using event data recorders (EDRs). Since drivers in emergency braking situations are motivated to hit the brake hard, it follows that drivers in emergency braking situations that commit a PM would likewise hit the accelerator hard, likely harder than accelerator pedal application during normal driving. Thus, the time-series accelerator pedal position and the derived accelerator pedal application rate were used to isolate accelerator misapplications. Additional strategic filters were applied based on characteristics observed from previous PM analyses to reduce false positive PM identifications.

Nested planetary gear trains, which consist of two integrated co-axial single-stage planetary gearsets, have recently been widely implemented in automobile transmissions and various other applications. In the current study, a non-destructive vibrational and acoustical monitoring technique is developed to detect a common type of gear grinding defect for a complex nested gear train structure. A nested gear train which has an unground pinion with unpolished teeth profile is used to exemplify the developed methodology. An experimental test stand with an open and vertical mounting configuration has been designed to acquire both vibrational and acoustical data. The measured data are investigated using several signal processing techniques to identify unground pinions in the gear system. A general frequency spectrum analysis is performed initially, which is then followed by a peak finding algorithm to identify the peaks in the spectrum.

Commercial vehicles require fast aftertreatment heat-up in order to move the SCR catalyst into the most efficient temperature range to meet upcoming NOX regulations. Today’s diesel aftertreatment systems require on the order of 10 minutes to heat up during a cold FTP cycle. The focus of this paper is to heat up the aftertreatment system as quickly as possible during cold starts and maintain a high temperature during low load, while minimizing fuel consumption. A system solution is demonstrated using a heavy-duty diesel engine with an end-of-life aged aftertreatment system targeted for 2027 emission levels using various levels of controls. The baseline layer of controls includes cylinder deactivation to raise the exhaust temperature more than 100° C in combination with elevated idle speed to increase the mass flowrate through the aftertreatment system. The combination yields higher exhaust enthalpy through the aftertreatment system.

This paper explains the basic principles behind two platform technologies that my research team has developed in the field of optical metrology and optical information processing: 1) high-speed 3D optical sensing; and 2) real-time 3D video compression and streaming. This paper will discuss how such platform technologies could benefit the automotive industry including in-situ quality control for additive manufacturing and autonomous vehicle systems. We will also discuss some of other applications that we have been working on such as crime scene capture in forensics.

Modern thermal propulsion systems (TPS) as part of hybrid powertrains are becoming increasingly complex. They have an increased number of components in comparison to traditionally powered vehicles leading to increased demand in packaging requirements. Many of the components in these systems relate to achieving efficiency gains, weight saving and pollutant reduction. This includes turbochargers and diesel or gasoline particulate filters for example and these are known to be very sensitive to inlet boundary conditions. When overcoming packaging requirements, sub-optimal flow distributions throughout the TPS can easily occur. Moreover, the individual components are often designed in isolation assuming relatively flat and artificially quiescent inlet flow conditions in comparison to those they are actually presented with. Thus, some of the efficiency benefits are lost through reduced component aerodynamic efficiency.

Diesel Cylinder Deactivation (CDA) has been shown in previous work to increase exhaust temperatures, improve fuel efficiency, and reduce engine-out NOx for engine loads up to 3 bar BMEP. The purpose of this study is to determine whether or not the turbocharger needs to be altered when implementing CDA on a diesel engine. This study investigates the effect of CDA on exhaust temperature, fuel efficiency, and turbocharger performance in a 15L heavy-duty diesel engine under low-load (0-3 bar BMEP) steady-state operating conditions. Two calibration strategies were evaluated. First, a “stay-hot” thermal management strategy in which CDA was used to increase exhaust temperature and reduce fuel consumption. Next, a “get-hot” strategy where CDA and elevated idle speed was used to increase exhaust temperature and exhaust enthalpy for rapid aftertreatment warm-up.