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This paper delves into the investigation of flatness-based active damping control for hybrid vehicle transmissions. The main objective is to improve the current in-production controller performances without the need for additional sensors or observers. The primary goals include improving torque setpoint tracking, enhancing robustness margins, and ensuring zero steady-state torque correction. The investigation proceeds in several steps: Initially, both the general differential flatness property and the identification of flat outputs in linear dynamical systems are revisited. Subsequently, the bond graph formalism is employed to deduce straightforwardly the dynamical equations of the system. Next, a new flat output of the vehicle transmission is identified and utilized to formulate the trajectory tracking controller to align with the required control objectives and to fulfill the system constraints.

This paper introduces a novel approach to modeling Torque Converter (TC) in conventional and hybrid vehicles, aiming to enhance torque delivery accuracy and efficiency. Traditionally, the TC is modelled by estimating impeller and turbine torque using the classical Kotwicki’s set of equations for torque multiplication and coupling regions or a generic lookup table based on dynamometer (dyno) data in an electronic control unit (ECU) which can be calibration intensive, and it is susceptible to inaccurate estimations of impeller and turbine torque due to engine torque accuracy, transmission oil temperature, hardware variation, etc. In our proposed method, we leverage an understanding of the TC inertia – torque dynamics and the knowledge of the polynomial relationship between slip speed and fluid path torque. We establish a mathematical model to represent the polynomial relationship between turbine torque and slip speed.

The tightening emissions regulations across the globe pose significant challenges to vehicle OEMs. As a result, OEMs are diversifying their powertrain solutions e.g., CNG/Propane based conventional powertrains, BEVs, H2 ICE, FCEV, etc. to meet these regulations. More recently, the ‘CARB Advanced Clean Trucks’ and ‘EPA GHG Phase 3’ regulations are forcing manufacturers to increasingly adopt zero tailpipe emission solutions. While passenger vehicle applications are trending towards a single consensus i.e., BEVs, the heavy-duty on-road applications are challenged with unique requirements of high payload capacity, higher range, lower sales volumes, higher durability, short refueling time, etc. These requirements are driving manufacturers to consider FCEV as an alternative powertrain solution to BEV specifically for higher payload capacity, and range applications.

This paper proposes an optimization-based transmission gear shifting strategy for electrified powertrains with a transmission. With the demand for reduced vehicle emissions, electrified propulsion systems have garnered significant attention due to their potential to improve vehicle efficiency and performance. An electrified propulsion system architecture of significance includes multiple electric motors and a transmission where some driveline actuators can transmit torque through changing gear ratios. If there is at least one electric motor arranged before the input of the transmission and at least one after the transmission output, a unique design opportunity arises to shift gears in the most energy efficient manner.

In this paper, a control strategy for state of charge (SOC) allocation using navigation data for Hybrid Electric Vehicle (HEV) propulsion systems is proposed. This algorithm dynamically defines and adjusts a SOC target as a function of distance travelled on-line, thereby enabling proactive management of the energy store in the battery. The proposed approach incorporates variances in road resistance and adheres to geolocation constraints, including ultra-low emission zones (uLEZ). The anticipated advantages are particularly pronounced during scenarios involving extensive medium-to-long journeys characterized by abrupt topological changes or the necessity for exclusive electric vehicle (EV) mode operation. This novel solution stands to significantly enhance both drivability and fuel economy outcomes.

Automotive Heating Ventilation and Air Conditioning (HVAC) system is essential in providing the thermal comfort to the cabin occupants. The HVAC noise which is typically not the main noise source in IC engine vehicles, is considered to be one of the dominant sources inside the electric vehicle cabin. As air is delivered through ducts and registers into the cabin, it will create an air-rush/broadband noise and in addition to that, any sharp edges or gaps in flow path can generate monotone/tonal noise. Noise emanating from the HVAC system can be reduced by optimizing the airflow path using virtual tools during the development stage. This paper mainly focuses on predicting the noise from the HVAC ducts and registers. In this study, noise simulations were carried-out with ducts and registers. A Finite Volume Method (FVM) based 3-dimensional (3D) Computational Fluid Dynamics (CFD) solver was used for flow as well as acoustic simulations.

The charge air cooler (CAC), which is placed between the compressor and the engine intake manifold (IM), is an important component in a turbocharged engine. It is essential to capture the temperature change, the pressure drop or the acoustical wave behavior of the charge air cooler in the one-dimensional(1D) simulation model for the predictive accuracy of engine performance and intake noise. In this paper, the emphasis is on the acoustic modeling of an intake manifold and charge air cooler assembly for the low frequency engine intake order noise. In this assembly, the core of the charge air cooler is embedded in the plenum of the intake manifold. The modeling and correlation process is comprised of three steps. First, the charge air cooler core is removed from the intake manifold and put into a rectangular box matching its envelope with a single air inlet and outlet, thereby simplifying the complex shape of the manifold with the different runner components.

The proliferation and increased complexity of electrified powertrains presents a challenge to the associated controls development. This paper outlines the strategy of common supervisory and domain torque management for such powertrains. The strategy covers the multitude of powertrain architectures that exist in the market today while maintaining the fundamental pillars of physics-based torque controls, state-of-the-art optimization methodologies, and common-core hybrid system constraints. The electrified powertrain torque controls that Stellantis LLC. uses include key constituents such as optimization of powertrain state that relate to optimum engine speed and transmission gear, optimization of engine and motor torques, engine start-stop management, and hybrid shift execution which manages powertrain state transitions by interacting with various external transmission systems. The common backbone of these constituents are the dynamic/kinematic equations of the powertrain.

Water fording events are one of the most challenging situations that vehicles undergo during their lifetime. During these events the underbody components (e.g. Front fascia, Bellypan, wheel liner etc.) are subject to very high loads. Typically, vehicle water fording tests are performed for various depths of water at prescribed vehicle speeds. Water fording tests are usually carried out during the proto phase of the vehicle development program to ensure acceptable performance. If issues are discovered, making changes to the fascia or body panels are typically very expensive. To avoid late changes, a fully virtual methodology was developed to facilitate vehicle water fording performance. The simulation is targeted to evaluate multiple aspects such as air induction system and estimation of hydrodynamic loads on body panel components.

As the automotive industry is quickly changing towards electric vehicles, we can highlight the importance of aerodynamics and its critical role in reaching extended battery ranges for electric cars. With all new smooth underbodies, a lot of attention has turned into the effects of rim designs and tires brands and the management of these tire wakes with the vehicle. Tires are one of the most challenging areas for aerodynamic drag prediction due to its unsteady behavior and rubber deformation. With the simulation technologies evolving fast regarding modeling spinning tires for aerodynamics, this paper takes the prior work and data completed by the authors and investigates the impact on the flow fields and aerodynamic forces using the most recent developments of an Immerse Boundary Method (IBM). IBM allows us to mimic realistically a rotating and deformed tire using Lattice Boltzmann methods.

Cooling airflow is an essential factor when it comes to vehicle performance and operating safety. In recent years, significant efforts have been made to maximize the flow efficiency through the heat exchangers in the under-hood compartment. Grille shutters, new fan shapes, better sealings are only some examples of innovations in this field of work. Underhood cooling airflow simulations are an integral part of the vehicle development process. Especially in the early development phase, where no test data is available to verify the cooling performance of the vehicle, computational fluid dynamics simulations (CFD) can be a valuable tool to identify the lack of fan performance and to develop the appropriate strategy to achieve airflow goals through the heat exchangers. For vehicles with heat exchangers in the underhood section the airflow through those components is of particular interest.

In a passenger car, suspension link bushings, engine and transmission mount bushings and bump-stops are made of elastomeric materials, to maximize the durability and comfort. Thus, deformation behavior of rubber and its durability is important for product design and development. In virtual engineering, simulating rubber fatigue is a complex exercise, since it needs right modeling strategy and coupon based testing material data. Principal stretches based Ogden model is used to characterize the hyper elastic deformation behavior of natural rubber. Fatigue crack growth approach used here for the fatigue analysis. Engine torque strut mount is used to control the engine and transmission fore aft motion and it is connected between body and Powertrain (PT) system. Powertrain events are predominant for damage contribution to mount failure. So, it is important to predict fatigue life of mount elastomer bushing under Powertrain loading.

Automobile hood design is driven by many factors, such as strict government regulations, fuel economy, weight, manufacturability, aerodynamic performance, aesthetics, structural integrity, and pedestrian safety standards. The requirement of improved fuel economy and safety regulations like pedestrian protection drive designers to reduce the thickness of the hood parts and use lighter materials. This leads to significant reduction in the hood stiffness. The hood needs to withstand steady and unsteady aerodynamic loads and meet deflection and vibration targets. The susceptibility of the hood to adverse aero load response is increased as the stiffness of the hood is reduced. The objective of this study is to develop a methodology to simulate hood behavior under transient aerodynamic loads in controlled environments. This study mainly focuses on developing fluid structure interaction methodology to simulate the behavior of the hood system under transient aerodynamic loads.

Reducing emissions and the carbon footprint of our society have become imperatives requiring the automotive industry to adapt and develop technologies to strive for a cleaner sustainable transport system and for sustainable economic prosperity. Electrified hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV) and range extender powertrains provide potential solutions for reducing emissions, but they present challenges in terms of thermal management. A key requirement for meeting these challenges is accurately to predict the thermal loading and temperatures of an internal combustion engine (ICE) quickly under multiple full-load and part-load conditions. Computational Fluid Dynamics (CFD) and thermal survey database methods are used to derive thermal loading of the engine structure and are well understood but typically only used at full-load conditions.

Stringent requirements for high fuel economy and energy efficiency mandate using increasingly complex vehicle thermal systems in most types of electrified vehicles (xEVs). Enabling the maximum benefits of such complex thermal systems under the full envelope of their operating modes demands designing complex thermal control systems. This is becoming one of the most challenging problems for electrified vehicles. Typically, the thermal systems of such vehicles have several modes of operation, constituting nonlinear multiple-input/multiple-output (MIMO) dynamic systems that cannot be efficiently controlled using classical or rule based strategies. This paper covers the different steps towards the design of a model-based control (MBC) strategy that can improve the overall performance of xEV thermal control systems. To achieve the above objective, the latter MBC strategy is applied to control cooling of the cabin and high voltage battery.

The automotive industry continues to develop new powertrain and vehicle technologies aimed at reducing overall vehicle-level fuel consumption. Specifically, the use of electrified propulsion systems, including electrified and electric drive units (EDU), is expected to play a significant role in helping OEMs meet fleet CO2 reduction targets for 2025 and beyond. The change to vehicles propelled by electrified powertrains leads to a reduction in vehicle noise levels. Despite the overall noise levels being low, the NVH behavior of such vehicles can be objectionable due to the presence of tonal noise coming from electric machines and geartrain components. In order to ensure customer acceptance of electrically propelled vehicles, it is imperative that these NVH challenges are understood and solved. Specifically, this paper discusses the EDU NVH development process. This includes considerations for CAE/test-based development and validation processes to ensure optimal NVH development.

The automotive industry continues to develop new powertrain and vehicle technologies aimed at reducing overall vehicle-level fuel consumption. Specifically, the use of innovative drivetrain technologies including conventional and electrified propulsion systems is expected to play an increasingly important role in helping OEMs meet fleet CO2 reduction targets for 2025 and beyond. NVH development for vehicles with electrified powertrains introduces new challenges, which need to be understood and solved. The electrified vehicle space spans variants from micro and mild hybrids all the way through plug-in hybrids and fully electric vehicles. In addition to conventional NVH development methodologies, active sound design (ASD) can play a crucial role to enhance the interior sound perception of such vehicles and hence, improve customer acceptance of new technologies. This paper will begin with an introduction to the NVH challenges posed by electrified vehicles.

For flows around a tire rotating over a ground plane, the Reynolds number is probably the most important parameter influencing the transition mechanism leading to flow separation from the tire surface, as it determines the viscous response of the boundary layer in the vortex-wall interaction. The present work investigates the effects of Reynolds number on an isolated tire model using a commercial Computational Fluid Dynamics (CFD) code. It validates the baseline simulation for this purpose against the Particle Image Velocimetry (PIV) data from Stanford University got using a Toyota Formula 1 race car tire model. Time-resolved velocity fields and vortex structures from the PIV data are used to correlate local and global flow phenomena to identify unsteady boundary-layer separation and the subsequent flow structures. The study will highlight the pre to post critical flow regimes where the aero coefficients and vortex structure will be studied.

Tire modeling has been an area of major research in automotive industries as the tires cause approximately 25% of vehicle drag. With the fast-paced growth of computational resources, Computational Fluid Dynamics (CFD) has evolved as an effective tool for aerodynamic design and development in the automotive industry. One of the main challenges in the simulation of the aerodynamics of tires is the lack of a detailed and accurate experimental setup with which to correlate. In this study, the focus is on the prediction of the aerodynamics associated with an isolated rotating Formula 1 tire and brake assembly. Literature has indicated differing mechanisms explaining the dominant features such as the wake structures and unsteadiness. Limited work has been published on the aerodynamics of a realistic tire geometry with specific emphasis on advanced turbulence closures such as the Detached Eddy Simulation (DES).

This paper will focus on automotive development highlights of FCA US LLC magnesium intensive closures components. Deploying lightweight materials is one of many key strategies that has been implemented to reduce vehicle mass and improve overall fuel economy while maintaining rigorous functional objective performance. This paper will outline some basic design and manufacturing considerations for magnesium closures. The development of the 2017 Chrysler Pacifica liftgate and 2018 Jeep® Wrangler swing gate along with the two generations of magnesium spare tire brackets will be the focus.