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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.

During driving conditions, when it is needed to transition from Electric Vehicle (EV) to Hybrid Vehicle operation, synchronization of the engine with the shaft and transmission is essential to enable clutch engagement and, subsequently, providing engine power to the wheels. Challenges arise when the engine must generate power to move itself and cannot rely on electric motors for precision. Cost-effective hybrid vehicle propulsion architectures which utilize small 12V belt-starter generators (BSGs) to initiate engine activation are inherently affected. In these situations, a speed profile that balance rapid response and control effort while considering system limitations to mitigate undesirable overshoots and delays, is required. This paper presents a Linear Quadratic Integral (LQI) approach to formulate a speed reference profile that ensures optimal engine behavior.

A variety of structures resonate when they are excited by external forces at, or near, their natural frequencies. This can lead to high deformation which may cause damage to the integrity of the structure. There have been many applications of external devices to dampen the effects of this excitation, such as tuned mass dampers or both semi-active and active dampers, which have been implemented in buildings, bridges, and other large structures. One of the active cancellation methods uses centrifugal forces generated by the rotation of an unbalanced mass. These forces help to counter the external excitation force coming into the structure. This research focuses on active force cancellation using centrifugal forces (CFG) due to mass imbalance and provides a virtual solution to simulate and predict the forces required to cancel external excitation to an automotive structure. This research tries to address the challenges to miniaturize the CFG model for a body-on-frame truck.

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.

The characterization of sheet metals under in-plane uniaxial bending is challenging due to the aspect ratios involved that can cause buckling. Anti-buckling plates can be employed but require compensation for contact pressure and friction effects. Recently, a novel in-plane bending fixture was developed to allow for unconstrained sample rotation that does not require an anti-buckling device. The objective of the present study is to design the sample geometry for sheared edge fracture characterization under in-plane bending along with a methodology to resolve the strains exactly at the edge. A series of virtual experiments were conducted for a 1.0 mm thick model material with different hardening rates to identify the influence of gage section length, height, and the radius of the transition region on the bend ratio and potential for buckling. Two specimen geometries are proposed with one suited for constitutive characterization and the other for sheared edge fracture.

Electrical steels are silicon alloyed steels that possess great magnetic properties, making them the ideal material choice for the stator and rotor cores of electric motors. They are typically comprised of laminated stacks of thin electrical steel sheets. An electric motor can reach high temperatures under a heavy load, and it is important to understand the combined effect of temperature and load on the electrical steel’s performance to ensure the long life and safety of electric vehicles. This study investigated the fatigue strength and failure behavior of a 0.27mm thick electrical steel sheet, where the samples were prepared by a stamping process. Stress-control fatigue tests were performed at both room temperature and 150°C. The S-N curve indicated a decrease in the fatigue strength of the samples at the elevated temperature compared to the room temperature by 15-25 MPa in the LCF and HCF regimes, respectively.

Strict environmental regulations are driving the automotive industry toward electric vehicles as they offer zero emissions. A key component in electric vehicles is the electric motor, where the stator and rotor are manufactured from stacks of thin electrical steel sheets. The electrical steel sheets can be cut in different ways, and the cutting methods may significantly affect the fatigue strength of the component. It is important to understand the effect of the cutting processes on the fatigue properties of electrical steel to ensure there is no premature failure of the electric motor resulting from an improper cutting process. This investigation compared the effect of three different edge preparation methods (stamping, CNC machining, and waterjet cutting) on the fatigue performance of 0.27mm thick electrical steel sheets. To investigate the effect of the edge finish on fatigue behavior, surface roughness was measured for these different samples.

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.

Many chassis and powertrain components in the transportation and automotive industry experience multi-axial cyclic service loading. A thorough load-history leading to durability damage should be considered in the early vehicle production steps. The key feature of rubber fatigue analysis discussed in this study is how to define local critical location strain time history based on nominal and complex load time histories. Material coupon characterization used here is the crack growth approach, based on fracture mechanics parameters. This methodology was utilized and presented for a truck engine mount. Temperature effects are not considered since proving ground (PG) loads are generated under isothermal high temperature and low frequency conditions without high amounts of self-heating.

Vibration shaker testing is a great tool of validating the vibration fatigue performance of automotive components & systems. However, the representative vibration schedule requires a pre-knowledge of the acceleration history for the test object, which usually is not available until the later development phase of a vehicle program when physical properties are available. Sometimes, a generic vibration schedule developed from the worst-case loading profiles are used with risk of lacking correlation with later full vehicle durability test such as Road Test Simulator (RTS) or Proving Ground (PG) road test due to the higher loading amplitude. This paper proposes a virtual accelerometer approach to collect acceleration responses of a component from a virtual vehicle model. First, a multiple body dynamic model will be produced for virtual load calculation over a series of digitalized virtual proving ground road profiles.

The Brake judder is a low-level vibration caused due to Disc Thickness Variation (DTV), Temperature, Brake Torque Variation (BTV), thermal degradation, hotspot etc. which is a major concern for the past decades in automobile manufacturers. To predict the judder performance, the modelling methods are proposed in terms of frequency and BTV respectively. In this study, a mathematical model is constructed by considering full brake assembly, tie rod, coupling rod, steering column, and steering wheel as a spring mass system for identifying judder frequency. Simulation is also performed to predict the occurrence of brake judder and those results are validated with theoretical results. Similarly, for calculating BTV a separate methodology is proposed in CAE and validated with experimental and theoretical results.

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.

ISO/SAE 21434 [1] Final International Standard was released September 2021 to great fanfare and is the most prominent standard in Automotive Cybersecurity. As members of the Joint Working Group (JWG) the authors spent 5 years developing the 84 pages of precise wording acceptable to hundreds of contributors. At the same time the auto industry had been undergoing a metamorphosis probably unmatched in its hundred-year history. A centerpiece of the metamorphosis is the adoption of the Agile development method to meet market demands for time-to-market and flexibility of design. Unfortunately, a strategic decision was made by the JWG to focus ISO/SAE 21434 on the V-Model method. Agile does not break ISO/SAE 21434. Agile is a framework that can be adapted to suit any process. In the end the goals are the same regardless of development method; security by design must be achieved.

The presence of residual stresses affects the fatigue response of welded components. In the present study of thick welded cantilever specimens, residual stresses were measured in two A36 steel samples, one in the as-welded condition, and one subjected to a short history of bending loads where substantial local plasticity is expected at the fatigue hot-spot weld toe. Extensive X-Ray Diffraction (XRD) measurements describe the residual stress state in a large region above the weld toe both in an untested as-welded sample and in a sample subjected to a short load history that generated an estimated 0.01 strain amplitude at the stress concentration zone at the weld toe. The results show that such a test will significantly alter the welding-induced residual stresses. Fatigue life prediction methods need to be aware that such alterations are possible and incorporate the effects of such cyclic stress relaxation in life computations.

Safety assurance is a central concern for the development and societal acceptance of automated driving (AD) systems. Perception is a key aspect of AD that relies heavily on Machine Learning (ML). Despite the known challenges with the safety assurance of ML-based components, proposals have recently emerged for unit-level safety cases addressing these components. Unfortunately, AD safety cases express safety requirements at the system level and these efforts are missing the critical linking argument needed to integrate safety requirements at the system level with component performance requirements at the unit level. In this paper, we propose the Integration Safety Case for Perception (ISCaP), a generic template for such a linking safety argument specifically tailored for perception components. The template takes a deductive and formal approach to define strong traceability between levels.

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.

Accurate prediction of in-vehicle powertrain bounce mode is necessary to ensure optimum responses are achieved at driver’s touch points during 4post shake or rough road shake events. But, during the early stages of vehicle development, building a detailed vehicle finite element (FE) model is not possible and often powertrain bounce modes are computed assuming the powertrain to be a stand-alone unit. Studies conducted on FE models of a large SUV with body on frame architecture showed that the stand-alone approach overestimates the powertrain bounce mode. Consequently, there is a need for a simplified version of vehicle model which can be built early on to compute powertrain modes. Previously, representing all the major components as rigid entities, simplified unibody vehicle models have been built to compute powertrain modes. But such an approach would be inaccurate here, for a vehicle with body on frame architecture due to the flexible nature of the frame (even at low frequencies).

As the move to decrease physical prototyping increases the need to virtually prototype vehicles become more critical. Assessing NVH vehicle targets and making critical component level decisions is becoming a larger part of the NVH engineer’s job. To make decisions earlier in the process when prototypes are not available companies need to leverage more both their historical and simulation results. Today this is possible by utilizing a hybrid modelling approach in an NVH Simulator using measured on road, CAE, and test bench data. By starting with measured on road data from a previous generation or comparable vehicle, engineers can build virtual prototypes by using a hybrid modeling approach incorporating CAE and/or test bench data to create the desired NVH characteristics. This enables the creation of a virtual drivable model to assess subjectively the vehicles acoustic targets virtually before a prototype vehicle is available.

In this study we collect and analyze data on how hands-free automated lane centering systems affect the controllability of a hazardous event during an operational situation by a human operator. Through these data and their analysis, we seek to answer the following questions: Is Level 2 and Level 3 automated driving inherently uncontrollable as a result of a steering failure? Or, is there some level of operator control of hazardous situations occurring during Level 2 and Level 3 automated driving that can reasonably be expected, given that these systems still rely on a driver as the primary fall back. The controllability focus group experiments were carried out using an instrumented MY15 Jeep® Cherokee with a prototype Level 2 automated driving system that was modified to simulate a hands-free steering system on a closed track with speeds up to 110kph. The vehicle was also fitted with supplemental safety measures to ensure experimenter control.