Browse Topic: Consumer preferences
The Mahindra XUV 3XO is a compact SUV, the first-generation of which was introduced in 2018. This paper explores some of the challenges entailed in developing the subsequent generation of this successful product, maintaining exterior design cues while at the same time improving its aerodynamic efficiency. A development approach is outlined that made use of both CFD simulation and Coastdown testing at MSPT (Mahindra SUV proving track). Drag coefficient improvement of 40 counts (1 count = 0.001 Cd) can be obtained for the best vehicle exterior configuration by paying particular attention to: AGS development to limit the drag due to cooling airflow into the engine compartment Front wheel deflector optimization Mid underbody cover development (beside the LH & RH side skirting) Wheel Rim optimization In this paper we have analyzed the impact of these design changes on the aerodynamic flow field, Pressure plots and consequently drag development over the vehicle length is highlighted. An interaction between grill closing and underfloor design of the same nominal dimensions is explored. Customers are increasingly demanding compact hatchback-like fuel consumption and CO2 emission limits are being made more stringent with upcoming revised CAFE norms. Therefore, it is essential to increase the efficiency of the vehicle and to minimize all energy losses. Aerodynamic drag constitutes ~30% of total energy consumption on WLTC cycle (excluding extra high speed phase) which is very significant. Compared to improvements in power train and vehicle mass, reduction of aerodynamic drag can be achieved at relatively low cost. For this vehicle, we demonstrate ways to improve the aero drag coefficient, 10% lower than the first-generation of XUV 3OO, thereby delivering ~2% Fuel Economy benefit to the customers.
With the advent of digital displays in driver cabins in commercial vehicles, drivers are being offered many features that convey some useful or critical information to drivers or prompt the driver to act. Due to the availability of a vast number of features, drivers face decision fatigue in choosing the appropriate features. Many are unaware of all available functionalities displayed in the Human Machine Interface (HMI) System, leading to a bare minimum usage or complete neglect of helpful features. This not only affects driving efficiency but also increases cognitive load, especially in complex driving scenarios. To alleviate the fatigue faced by drivers and to reduce the induced lethargy to choose appropriate features, we propose an AI driven recommendation agent/system that helps the driver choose the features. Instead of manually choosing between multiple settings, the driver can simply activate the recommendation mode, allowing the system to optimize selections dynamically. The novelty of this proposal focuses on introducing Intelligence in HMI Systems in such a way that it will maximize the operational usage and reduce decision fatigue in drivers. In this paper, we aim to propose a novel metric - “Decision fatigue index” to conceptualize both – the reduction in driver's cognitive load and AI models to capture, train based on the data from the driver preferences, road conditions, vehicle dynamics and user customizations. The most relevant mitigation/intervention strategies will be augmented in the HMI, which enhances ease of use, improves safety, and ensures that drivers receive the most relevant assistance.
The implementation of active sound design models in vehicles requires precise tuning of synthetic sounds to harmonize with existing interior noise, driving conditions, and driver preferences. This tuning process is often time-consuming and intricate, especially facing various driving styles and preferences of target customers. Incorporating user feedback into the tuning process of Electric Vehicle Sound Enhancement (EVSE) offers a solution. A user-focused empirical test drive approach can be assessed, providing a comprehensive understanding of the EVSE characteristics and highlighting areas for improvement. Although effective, the process includes many manual tasks, such as transcribing driver comments, classifying feedback, and identifying clusters. By integrating driving simulator technology to the test drive assessment method and employing machine learning algorithms for evaluation, the EVSE workflow can be more seamlessly integrated. But do the simulated test drive results accurately reflect real-world impressions? This paper compares virtual test drive results with road test results and explores to what extent this unique method can be utilized to improve the EVSE tuning process.
E-mobility is revolutionizing the automotive industry by improving energy-efficiency, lowering CO2 and non-exhaust emissions, innovating driving and propulsion technologies, redefining the hardware-software-ratio in the vehicle development, facilitating new business models, and transforming the market circumstances for electric vehicles (EVs) in passenger mobility and freight transportation. Ongoing R&D action is leading to an uptake of affordable and more energy-efficient EVs for the public at large through the development of innovative and user-centric solutions, optimized system concepts and components sizing, and increased passenger safety. Moreover, technological EV optimizations and investigations on thermal and energy management systems as well as the modularization of multiple EV functionalities result in driving range maximization, driving comfort improvement, and greater user-centricity. This paper presents the latest advancements of multiple EU-funded research projects under the Horizon Europe framework and showcases their complementarities to address the European priorities as identified in the 2Zero SRIA, namely EFFEREST, MINDED, and SmartCorners. EFFEREST targets energy efficiency, comfort, safety, and affordability of EVs through considering knowledge from real-fleet behavior and personalization of data. MINDED aims to maximize EV’s driving range by improving the thermal- and energy management of an electric minibus to reduce energy consumption while optimizing thermal comfort, and therefore directly impacting the user acceptance. SmartCorners provides scalable, flexible, and user-centric smart corner systems including e-axles and e-corners based on in-wheel powertrains. SmartCorners aims at introducing smart corner systems based on in-wheel powertrains as underlaying technology toward software-defined vehicles, enabling rightsizing, holistic optimization, innovative fault mitigation and actuator allocation strategies as well as more efficient, adaptive, predictive, and personalized system operation.
This SAE Edge Research Report explores advancements in next-generation mobility, focusing on digitalized and smart cockpits and cabins. It offers literature review, examining current customer experiences with traditional vehicles and future mobility expectations. Key topics include integrating smart cockpit and cabin technologies, addressing challenges in customer and user experience (UX) in digital environments, and discussing strategies for transitioning from traditional vehicles to electric ones while educating customers. User Experience for Digitalized and Smart Cockpits and Cabins of Next-gen Mobility covers both on- and off-vehicle experiences, analyzing complexities in developing and deploying digital products and services with effective user interfaces. Emphasis is placed on meeting UX requirements, gaining user acceptance, and avoiding trust issues due to poor UX. Additionally, the report concludes with suggestions for improving UX in digital products and services for future mobility, offering a summary of insights and actionable recommendations to enhance the UX in automotive technologies. Understanding the correlation between UX, user acceptance, and market success from a UX, design, and human-factor perspective will assist companies in creating customer-facing next-gen products. Click here to access the full SAE EDGETM Research Report portfolio.
Letter from the Guest Editors
Sometimes, I cringe; sometimes, I just listen and wonder. These past few months have given us all a lot to think about in the automotive space, and it's clear now that the coming years will keep the foot down on the accelerator when it comes to the dramatic changes we've experienced this past decade. One thing that stood out to me in various recent conversations is that there's a widening gulf opening between Chinese automakers and the rest of the world. This isn't exactly news, and this column isn't meant to monger any fears. It's just a bit of off-the-cuff reporting that sheds a bit of light on the level of the challenges we face. As you can read in Chris Clonts' excellent report further in this issue about the warning that Voltaiq's CEO gave at The Battery Show this October, the U.S. is in serious danger of falling well behind Chinese competitors in the EV battery race (Michael Robinette tackles similar ground through a tariff lens in this month's Supplier Eye). But that message was obvious to anyone who meandered through the expo hall during the show. The spacious Huntington Place (neé Cobo Hall) was filled by more battery suppliers and tech companies than I could count (organizers said it was over 1,150), many with a Chinese connection. Those of us who remember the busy days when the Detroit Auto Show covered a similar footprint were astonished by the variety on display, and almost all of it was EV-focused. The Battery Show proved that there's good battery development work happening in North America and Europe, but it was hard to ignore just how present China and Chinese-related companies are in the electrification mission.
This study aims to explore the multifaceted influencing factors of market acceptance and consumer behavior of low-altitude flight services through online surveys and advanced neuroscientific methods (such as functional magnetic resonance imaging fMRI, electroencephalography EEG, functional near-infrared spectroscopy fNIRS) combined with artificial intelligence and video advertisement quantitative analysis. We conducted an in-depth study of the current trends in low-altitude flight vehicle development and customer acceptance of low-altitude services, focusing particularly on the survey methods used for market acceptance. To overcome the influence of strong opinion leaders in volunteer group experiments, we designed specialized surveys targeting broader online and social media groups. Utilizing specialized knowledge in aviation psychology, we designed a distinctive questionnaire and, within just 7 days of its launch, gathered a significant number of valid responses. The data was then analyzed using AI to provide original, insightful data on the acceptance of low-altitude services. Furthermore, we addressed the limitations of traditional manual survey methods by designing an advanced system combining EEG and AI analysis to automatically generate surveys by measuring neural and physiological responses while subjects watched video advertisements for low-altitude services. Our research offers a comparison with existing online survey forms and proposes specific predictions to potentially improve the accuracy of online surveys.
Vehicle quality and affordability will always be the most distinguishing summative characteristics in a fully saturated and highly competitive market. While vehicle quality differentiates between brands in any market segment, affordability remains the key decisive factor for many buyers in each segment. Equally important, affordability is a critical factor in achieving equity in transportation by providing reasonably priced vehicles with quality fitting the needs of different users. Keeping in mind that the cost of quality is usually in conflict with affordability, the main challenge during the different phases of the vehicle design and development process from inception to production becomes the achievement of the multi-objective conflicting goals of maximizing affordability and quality at the same time. In this paper, guided by quality characteristics framework, that accounts for affordability as a context and structured participation of the customers during the vehicle realization process, the maximization of quality achievements within the preestablished affordability targets throughout the process is studied and discussed. By establishing and monitoring affordability and quality targets by the quality management system along with integrating customers’ participations at critical phases during the realization process from inception to production, the necessary inputs for decision making to deconflict the multi-objective goals of maximizing quality and affordability throughout the product design and development process could be achieved. To ensure customer satisfaction for quality and stay within targeted affordability, changes to the quality management system and product development process traditional customer participation are proposed. These changes are necessary to integrate affordability as the quality context in the traditional quality management system and include systematic customers’ participation at the end of selected key stages of the vehicle realization. By adding customers’ reviews at critical phases during the realization process, the needed customers’ inputs to achieve the desired vehicle quality within the established tolerances and affordability targets could be achieved.
Customer preference towards quieter vehicles is ever-increasing. Exhaust tailpipe noise is one of the major contributors to in-cab noise and pass-by-noise of the vehicle. This research proposes a silencer with an integrated acoustic valve to reduce exhaust tailpipe noise. Incident exhaust wave coming from the engine strikes the acoustic valve and generates reflected waves. Incident waves and reflected waves cancel out each other which results in energy loss of the exhaust gas. This loss of energy results in reduced noise at the exhaust tailpipe end. To evaluate the effectiveness of the proposed silencer on the vehicle, NVH (Noise, vibration, and harshness) performance of the proposed silencer was compared with the existing silencer which is without an acoustic valve. A CNG (Compressed natural gas) Bus powered by a six-in-line cylinder engine was chosen for the NVH testing. After NVH evaluation, it was found that when using the proposed silencer, overall exhaust tailpipe orifice noise is reducing by 4-5 dB throughout the engine rpm range. In-cab noise at DEL (Driver ear level) is reducing by 2 dB throughout the engine rpm range except for 1200-1400 rpm range. Pass-by noise is reducing by 1 dB when vehicle is running in 3rd gear and it is reducing by 3 dB when vehicle is running in 4th gear.
Engineers like to know what customers think about a vehicle. Now, drivers of the all-electric Ford F-150 Lightning and Mustang Mach-E can oblige via a new system that channels select customer comments to engineers. F-150 Lightning fullsize pickup truck and Mustang Mach-E SUV owners in the U.S. can pass along opinions via a 45-second voice message after selecting “record feedback” through the settings-general menu on the infotainment touchscreen. “We want to hear the customer's voice. Ford does customer clinics and events, but this is a different way to capture customer feedback,” Donna Dickson, chief engineer of the Ford Mustang Mach-E, said in an interview with SAE Media.
Optimal Vehicle Dynamics is one of the key metrics that all Vehicle Manufacturers strive to achieve. The metrics vary from customer to customer and vehicle to vehicle. The vehicle dynamics represent the DNA of the car and the manufacturer. The challenge with the current state of pre-autonomy always is to achieve the state of vehicle dynamics that delivers stability/safety yet the responsiveness needed. In addition, there are always tradeoffs between ride/NVH and handling, where vehicle manufacturers end up sacrificing one for the other. The paper establishes the baseline of electrification advantages to address the past vehicle dynamics challenges and then discusses how the traditional vehicle dynamics design and metrics will evolve as the vehicle architecture migrates from mechanization/electrification to level 4/5 Autonomy. Customer preferences and demands will change with Autonomy.
The automotive industry is going through one of its greatest restructuring, the migration from internal combustion engines to electric powered / internet connected vehicles. Adapting to a new consumer who is increasingly demanding and selective may be one of the greatest challenges of this generation, Original Equipment Manufacturers (OEM) have been struggling to keep offering a diversified variety of features to their customers while also maintaining its quality standards. The vehicles leave the factory with an embedded SIM Card and a telematics module, which is an electronic unit to enable communication between the car, data center. Connected vehicles generate tens of gigabytes of data per hour that have the potential to be transformed into valuable information for companies, especially regarding the behavior and desires of drivers. One of the techniques used to gather quality feedback from the customers is the NPS it consists of open questions focused on top-of-mind feedback. Here is where AI and ML comes into play, using NLP and several other computational techniques to download, extract, structure, read, process, understand and categorize all this data into specific predetermined categories, allowing engineers to accelerate fixing quality issues and improving user experience. The ML model developed in this article identify costumer complains in an enormous data lake and groups them into categories. After a significative amount of data is collected and grouped into it enables the algorithm to predict future trends and together with real time connected vehicle data the model can alert the responsible engineers to develop an action to solve the problem without more customers even actually experience the failure. The ML algorithm is still on its development phase, but the initial results are promising, we have successfully processed more them 6 millioncustomers feedback finding problems with precision and accuracy close to 90%.
During the early phase of vehicle development, one of the key design attributes to consider are the interior storages for occupants. Internal storage is the pillar that is responsible for user’s comfort and make into customer comfort needs in engineer metrics. Therefore, it is one of the key requirements to be considered during the vehicle design. The vehicle has some interior storages, like storages on door trim, floor console and IP and to define the best solution for the customer, engineering team has certain internal vehicle characteristics such as the volume and size of storage are engineer metrics that influence the perception of comfort for occupants. One specific characteristic influencing satisfaction is the glove box volume, which is the subject of this paper. The objective of this project is to analyze the relationship between the glove box volume with the occupant’s satisfaction under real world driving conditions, based on research, statistical data analysis and dynamic clinics.
During the early phase of vehicle development, one of the key design attributes to consider is the inner comfort for occupants. Internal spaciousness is the pillar that is responsible for user’s comfort and make into customer comfort needs in engineer metrics. Therefore, it is one of the key requirements to be considered during the vehicle design. Certain internal vehicle characteristics such as the size of shoulder room and the knee clearance are engineer metrics that influence the occupants’ perception for comfort. One specific characteristic influencing satisfaction is the headroom, which is the subject of this paper. The objective of this project is to analyze the relationship between the second row’s vehicle headroom with the occupant’s satisfaction under real world driving conditions, based on research, statistical data analysis and dynamic clinics.
Reducing weight from components and systems is a major trend in passenger vehicles to boost fuel efficiency and driving range - it's not a strategy typically associated with construction machinery and stationary applications. Liebherr Components contends that such off-highway applications also can benefit from utilizing lighter-weight components and has spent years developing the expertise and production capabilities to add them to its hydraulics portfolio. Liebherr recently revealed “hybrid” hydraulic cylinders - components made of steel but wrapped in carbon-fiber-reinforced plastic (CFRP) - that can be up to 50% lighter than traditional all-steel cylinders. Depending on the application and customer preference, the weight savings can increase operating speeds, allow larger attachments and booms, and raise payloads - or, as in road-going vehicles, reduce CO2 emissions and fuel consumption during operation, the company said.
Automated-driving and ADAS functionalities continue to influence some of the latest cabin safety and materials trends. Evolving market realities have OEMs and automated-driving system developers adjusting once-aggressive timelines for deploying high-level driving automation. But new materials and safety technology for vehicle interiors continue to be influenced by advancing AV and ADAS functionalities. Regardless of how much driving automation is at play, vehicle cabins are evolving because of the possibilities - and challenges - automation and ADAS present. An array of launching or soon-to-arrive safety features, driver-information technology and materials innovations don't need AV applications as a reason for being, however. Drew Winter, Informa Tech Automotive's principal analyst - Cockpit of the Future, said that some of the feature and safety requirements of electric-vehicle and younger-demographic customers align with the technology directions for AVs and ADAS. New sustainable upholstery choices are a feature many current EV and young buyers desire, for example. Those same types of materials may also better address the durability and serviceability needs of automated shuttles and robotaxis.
The automotive industry is facing new emission regulations, changing customer preferences and technology disruptions. All have in common, that external aerodynamics plays a crucial role to achieve emission limits, reduce fuel consumption and extend electric driving range. Probably the most challenging components in terms of numerical aerodynamic drag prediction are the wheels. Their contribution to the overall pressure distribution is significant, and the flow topology around the wheels is extremely complicated. Furthermore, deltas between different rim designs can be very small, normally in the range of only a few drag counts. Therefore, highly accurate numerical methods are needed to predict rim rankings and deltas. This paper presents experimental results of four different production rim designs, mounted to a modified production car. An accurate representation of the loaded, deformed tire geometry is used in all calculations for comparable conditions between wind tunnel and CFD. Different simulation approaches are compared and analyzed to measured rim rankings and deltas. A special meshing strategy is introduced to reduce the influence of mesh changes on the flow field to a minimum. A steady state simulation approach in combination with a moving reference frame model is able to capture the delta between the best and worst rim design. The rim position has a non-negligible influence when using this frozen rotor method and needs to be considered. Transient scale resolving simulations with real motion of the rims remove the limitations of steady state. Ranking and deltas are accurately predicted for all four rims by the simulations.
The need to develop genuine ceramic composites for PV applications arose to overcome the challenges associated with traditional semi-metallic pads. The main focus is to achieve better performance, low noise, better pad and rotor wear, and low dust compared to semi- metallic pads. In general, brake pads convert kinetic energy to thermal energy through friction, and operating temperature in semi-metallic brake pads is higher due to the presence of steel having high thermal conductivity. Over the last decade, the customer preference has moved over to ceramic pads due to light coloured pad surface, low rotor and pad wear and low dust compared to semi-metallic pads. The traditional steel has been replaced by Aramid, engineered ceramic fibre, potassium titanate (TISMO D), lapinus fibre (RB 250) to impart similar/better performance. The current work investigates the characterisation of genuine ceramic and semi-metallic composites. Three genuine ceramic and one semi-met composite have been designed and evaluated for physical, mechanical and performance properties. All the composites have been tested on brake inertia dynamometer for AK Master (SAE J2522), AK Noise (SAEJ2521) and Wear (SAE J2707B) using a Volkswagen Golf calliper. The type of composite significantly influences friction, pad wear, rotor wear, noise and physical properties. Based on selective testing, it has been concluded that genuine ceramic composites have moderate friction, whereas friction level is higher in the semi-met composite. The pad and rotor wear rate of genuine ceramic composites is significantly lower as compared to semi-met. The noise and vibration properties of genuine ceramic pads are better than semi- met composite. The ceramic pads are also scorched for a better initial bite.
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