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Through real-time online optimization, the full potential of the performance and energy efficiency of multi-gear, multi-mode, series–parallel hybrid powertrains can be realized. The framework allows for the powertrain to be in its most efficient configuration amidst the constantly changing hardware constraints and performance objectives. Typically, the different gears and hybrid/electric modes are defined as discrete states, and for a given vehicle speed and driver power demand, a formulation of optimization costs, usually in terms of power, are assigned to each discrete states and the state which has the lowest cost is naturally selected as the desired of optimum state. However, the optimization results would be sensitive to numerical exactitude and would typically lead to a very noisy raw optimum state. The generic approach to stabilization includes adding hysteresis costs to state-transitions and time-debouncing.

Brake assemblies are an essential part of any vehicle, and their effective functioning is critical for the safety and comfort of passengers. The surface roughness of brake components plays a vital role in figuring out their tribological and NVH (Noise, Vibration, and Harshness) behavior. It is essential to understand the impact of surface roughness on brake performance to ensure efficient braking and it has been a topic of interest in the automotive industry. In this study, the influence of surface roughness on the wear, and noise characteristics of a brake assembly has been investigated. The study also provides insights into the relationship between surface roughness, frictional behavior, and NVH performance, which can be used to improve the design and manufacturing of brake assemblies. The brake assembly includes of a disc, caliper, and brake pads, which work together to convert the kinetic energy of the vehicle into heat energy, has been considered in this study.

The automotive industry is moving towards larger SUVs and also electrification is a need to meet the carbon neutrality target. As a result, we see an increase in overall gross vehicle weight (GVW), with the additional weight coming from the HV battery pack, electric powertrain, and other electrical systems. Tow-eye is an essential component that is provided with every vehicle to use for towing during an emergency vehicle breakdown. The tow-eye is usually connected to the retainer/sleeve available in the bumper system and towed using the recovery vehicle or other car with towing provision. Therefore, the tow-eye should meet the functional targets under standard operating conditions. This study is mainly for cars with bumper and tow-eye sleeves made of aluminum which is used in the most recent development of vehicles for weight-saving opportunities. Tow-eye systems in aluminum bumpers are designed to avoid any bending or buckling of the sleeve during towing for whatever the GVW loads.

Cargo box is one of the indispensable structures of a pickup truck which makes it capable of transporting heavy cargo weights. This heavy cargo weight plays an important role in durability performance of the box structure when subjected to road load inputs. Finite element representation for huge cargo weight is always challenging, especially in a linear model under dynamic proving ground road load durability analysis using a superposition approach. Any gap in virtual modeling technique can lead to absurd cargo box modes and hence durability results. With the existing computer aided engineering (CAE) approach, durability results could not correlate much with physical testing results. It was crucial to have the right and robust CAE modeling technique to represent the heavy cargo weight to provide the right torsional and cargo modes of the box structure and in turn good durability results.

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.

For the designing of world class vehicles, ride comfort is one of the criteria that vehicle manufacturers are constantly trying to improve. The automotive seating system is an important sub-system in a vehicle that contributes to the ride comfort of the vehicle occupants. Seat vibrations are perceived by the occupants and make them feel uncomfortable during driving conditions. These vibrations are majorly transferred from engine and road excitation loads. For road excitation loads, the road testing may not be accurately repeatable, and measurements based on four post shakers are used to assess the discomfort. The major challenges for the vehicle manufactures is the availability of physical prototypes at an early stage of vehicle development and any changes in the design due to test validation leads to huge cost and time.

Vehicle suspension parts are subjected to variable road loads, manufacturing process variation and high installation loads in assembly process. Seam welding can be considered as such process to connect more components and parts. Typical in a Mc Pherson suspension system stabilizer bar link is connected to the strut assembly through ball stud and clamped to a bracket welded to the outer strut tube. Cracks have been observed in the stabilizer bar link bracket welds of vehicles in the field, effecting the functionality of the suspension system. During preliminary phase of product development CAE assessment of the seam weld is carried out against road load data, if the design does not meet the targets enabler studies are carried out in an iterative approach. Various design variables (control factors) can be considered to carry out the iterations.

Design for Six Sigma (DFSS) is an essential tool and methodology for innovation projects to improve the product design/process and performance. This paper aims to present an application of the DFSS Taguchi Method for an automotive/vehicle component. High-Pressure Vacuum Assist Die Casting (HPVADC) technology is used to make Cast Aluminum Front Shock Tower. During the vehicle life, Shock Tower transfers the road high impact loads from the shock absorber to the body structure. Proving Ground (PG) and washout loads are often used to assess part strength, durability life and robustness. The initial design was not meeting the strength requirement for abusive washout loads. The project identified eight parameters (control factors) to study and to optimize the initial design. Simulation results confirmed that all eight selected control factors affect the part design and could be used to improve the Shock Tower's strength and performance.

Vibrations affect vehicle occupants and should be prevented early in design process. Powertrain (PT) wiggle is one of the well-known issues. It is the 3rd order lateral vibration, forced by half shaft inner LH/RH plunging tripod joints [1,2]. Lateral PT resonance (7-15Hz) occurs at certain vehicle speed during acceleration and may excite lateral, pitch and roll PT modes. Typically, PT wiggle occurs in speed range of 5-25kph. Vibration is noticeable on driver and passenger seats mostly in lateral direction. The inner half shaft joints are the major source of vibration. Unfortunately, existing MBD tools like Adams [3] are missing detailed tripod joint representation because of complex mechanical interactions inside the joint. At least three sliding contacts between tripod rollers and joint housing, lubricant inside the can and combination of rotation and plunging make the modeling too complicated.

Simplified vehicle dynamics models used to study the driveline durability are typically limited to the longitudinal dynamics and do not account for vertical and pitch dynamics. The influence of suspension on the vehicle ride and handling characteristics is studied extensively in the literature but its impact on the driveline torques is often not considered. In this paper, an effort is made to investigate the influence of suspension compliance on the driveline torque using a planar (longitudinal, pitch and vertical) vehicle dynamics model. An AWD vehicle is studied to understand its impact on the torque levels of both axles (primary and secondary). Subsequently the planar dynamics is explored in the context of anti-squat/anti-dive suspension. The primary focus of the paper is to predict the driveline torque.

The performance and durability of the lead acid battery is highly dependent on the internal battery temperature. The changes in internal battery temperatures are caused by several factors including internal heat generation and external heat transfer from the vehicle under-hood environment. Internal heat generation depends on the battery charging strategy and electric loading. External heat transfer effects are caused by customer duty cycle, vehicle under-hood components and under-hood ambient air. During soak conditions, the ambient temperature can have significant effect on battery temperature after a long drive for example. Therefore, the temperature rise in a lead-acid battery must be controlled to improve its performance and durability. In this paper a thermal model for lead-acid battery is developed which integrates both internal and external factors along with customer duty cycle to predict battery temperature at various driving conditions.

In this paper we present an integrated approach which combines analysis of the effect of simultaneous variations in model input parameters on component or system temperatures. The sensitivity analysis can be conducted by varying model input parameters using specific values that may be of interest to the user. The alternative approach is to use a structured set of parameters generated in the form of a DFSS DOE matrix. The matrix represents a combination of simulation conditions which combine the control factors (CF) and noise factors. CF’s are the design parameters that the engineer can modify to achieve a robust design. Noise factors include parameters that are outside the control of the design engineer. In automotive thermal management, noise factors include changes in ambient temperature, exhaust gas temperatures or aging of exhaust system or heat shields for example.

A cargo box is a key structure in a pickup truck which is used to hold various items. Therefore, a cargo box must be durable and robust under different ballast conditions when subjected to road load inputs. This paper discusses a Design for Six Sigma (DFSS) approach to improve the durability of cargo box panel in its early development phase. Traditional methods and best practices resulted in multiple iterations without an obvious solution. Hence, DFSS tools were proposed to find a robust and optimum solution. Key control factors/design parameters were identified, and L18 Orthogonal Array was chosen to optimize design using CAE tools. The optimum design selected was the one with the minimum stress level and the least stress variation. This design was confirmed to have significant improvement and robustness compared to the initial design. DFSS identified load paths which helped teams finally come up with integrated shear plate to resolve the durability concern.

An objective evaluation of ground vehicle performance is a challenging task. This is further exacerbated by the increasing level of autonomy, dynamically changing the roles and capabilities of these vehicles. In the context of decision making involving these vehicles, as the capabilities of the vehicles improve, there is a concurrent change in the preferences of the decision makers operating the vehicles that must be accounted for. Decision based methods are a natural choice when multiple conflicting attributes are present, however, most of the literature focuses on static preferences. In this paper, we provide a sequential Bayesian framework to accommodate time varying preferences. The utility function is considered a stochastic function with the shape parameters themselves being random variables. In the proposed approach, initially the shape parameters model either uncertain preferences or variation in the preferences because of the presence of multiple decision makers.

It is a challenging task to find an optimal design concept for a truck frame structure given the complexity of loading conditions, vehicle configurations, packaging and other requirements. In addition, there is a great emphasis on light weight frame design to meet stringent emission standards. This paper provides a framework for fast and efficient development of a frame structure through various design phases, keeping durability in perspective while utilizing various weight reduction techniques. In this approach frame weight and stiffness are optimized to meet strength and durability performance requirements. Fast evaluation of different frame configurations during the concept phase (I) was made possible by using DFSS (Design for Six Sigma) based system synthesis techniques. This resulted in a very efficient frame ladder concept selection process.

Nowadays development of automotive HVAC is a challenging task wherein thermal comfort and safety are very critical factors to be met. HVAC system is responsible for the demisting and defrosting of the vehicle’s windshield and for creating/maintaining a pleasing environment inside the cabin by controlling airflow, velocity, temperature and purity of air. Fog or ice which forms on the windshield is the main reason for invisibility and leads to major safety issues to the customers while driving. It has been shown that proper clear visibility for the windshield could be obtained with a better flow pattern and uniform flow distribution in the defrost mode of the HVAC system and defrost duct. Defroster performance has received significant attention from OEMs to meet the specific global performance standards of FMVSS103 and SAE J902. Therefore, defroster performance is seriously taken into consideration during the design of HVAC system and defroster duct.

Geometry Tree is a term describing the product assembly structure and the manufacturing process for the product. The concept refers to the assembly structure of the final vehicle (the Part Tree) and the assembly process and tools for the final product (the Process Tree). In the past few years, the Geometry Tree-based quality process was piloted in the FCA US LLC assembly plants and has since evolved into a standardized quality control process. In the Part Tree process, the coordinated measurements and naming convention are enforced throughout the different levels of detailed products to sub-assemblies and measurement processes. The Process Tree, on the other hand, includes both prominently identified assembly tools and the mapping of key product characteristics to key assembly tools. The benefits of directly tying critical customer characteristics to actual machine components that have a high propensity to influence them is both preventive and reactive.

Vehicle suspension parts are subjected to variable road loads, manufacturing process variation and high installation loads in assembly process. These parts must be robust to usage conditions to function properly in the field. Design for Six Sigma (DFSS) tools and Taguchi Method were used to optimize initial rear suspension trailing arm design. Project identified key control factor/design parameters, to improve part robustness at the lowest cost. Optimized design performs well under higher road loads and meets stringent durability requirements. This paper evokes use of Taguchi Method to design robust rear suspension trailing arm and study effect of selected design parameters on robustness, stress level/durability and part cost.

The development of complex engineering systems often encounters various challenges in terms of meeting New Product Development (NPD) assigned budget, launch time, and system performance goals. Most of the NPD processes have been experiencing challenges to meet these goals within an increasingly competitive global market environment. These challenges become more complicated to manage when the development process is long with different sources of uncertainty. Despite decades of industrial experience and academic research efforts in managing NPD processes, it is observed that designing and developing increasingly complex systems, e.g., automotive, is still subjected to significant cost overrun, schedule delays, and functional issues during early design stages. To provide a Reliability Growth Planning (RGP) model, several inputs are required, e.g., the initial reliability estimation, the reliability goal, test recourses, and the duration of the design or test period.

There have been multiple studies on the effect of vehicle impact pulses on occupant responses, and studies on the previous and current US NCAP (New Car Assessment Program) vehicle pulses. This paper analyzes 35 mph (56.3 kph) front impact vehicle pulses and occupant responses in US NCAP tests conducted by the NHTSA from 2011 to 2019. Based on the occupant response analysis, a simple generic occupant restraint force-relative displacement model has been created. This generic model captures the fundamental restraint characteristics of the vehicles in the recent years, and together with the vehicle pulse, they provide several occupant response predictors. Furthermore, this paper proposes a new pulse severity metric PSD (Pulse Severity by Displacement) based on the vehicle impact data statistics, and uses the pulse severity to compare with other pulse severity definitions.