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In this paper, an approach to analyze voice recognition data to understand how customers use voice recognition systems is explored. The analysis will help identify ASR failures and usability related issues that customers encounter while using the voice recognition system. This paper also examines the impact of these failures on the individual speech domains (media control, phone, navigation, etc.). Such information can be used to improve the current voice recognition system and direct the design of future systems. Infotainment system logs, audio recordings of the voice interactions, their transcriptions and CAN bus data were identified to be rich sources of data to analyze voice recognition usage. Infotainment logs help understand how the system interpreted or responded to customer commands and at what confidence level.

Closures systems performance is a trade-off between NVH (Noise, Vibration and Harshness) and DCE (Door Closing Efforts) requirements. Dynamic sealing performance and sheet metal rigidity are the key contributors for a stable system. The seals actuate like a spring on the system. Higher seal load is good for NVH performance, adding more dumping to the system, but it will negatively affect DCE, as it will demand additional energy to close the system. Nominal seal load must be defined to achieve a balance between these attributes. This study is about dynamic sealing profiles with variable seal load, which provides tunable solutions to address the trade-off between NVH and DCE on the side doors or rear closures. Dynamic sealing weatherstrips are made of sponge EPDM extruded profiles with a specified load, defined by its CLD (Compression Load Deflection), which is given by the cross section design.

Investing in quality as added value to products becomes a means of guaranteeing satisfaction as well as customer loyalty, making it competitive in its respective segment. In the automotive business, this has not been different, It can observed a progress in the perception and customers demand in quality in the last few years. At the same time, that the industries need to guarantee the cost and time of response to the dissatisfaction of the customers. In this project, was possible to implement a locking door concept, with an effective solution to the door vibration problem in a B platform, vehicle model in South America.

This paper summarizes the development of a wireless message from infrastructure-to-vehicle (I2V) for safety applications based on Dedicated Short-Range Communications (DSRC) under a cooperative agreement between the Crash Avoidance Metrics Partners LLC (CAMP) and the Federal Highway Administration (FHWA). During the development of the Curve Speed Warning (CSW) and Reduced Speed Zone Warning with Lane Closure (RSZW/LC) safety applications [1], the Basic Information Message (BIM) was developed to wirelessly transmit infrastructure-centric information. The Traveler Information Message (TIM) structure, as described in the SAE J2735, provides a mechanism for the infrastructure to issue and display in-vehicle signage of various types of advisory and road sign information. This approach, though effective in communicating traffic advisories, is limited by the type of information that can be broadcast from infrastructures.

SiC devices have inherent fast switching capabilities due to their superior material properties, and are considered potential candidates to replace Si devices for traction inverters in electrified vehicles in future. However, due to the comparatively low gate threshold voltage, SiC devices may encounter oscillatory false triggering especially during fast switching. This paper analyzed the causes of false triggering, and also studied the impact of a critical parasitic parameter - common source inductance. It is shown that crosstalk is the main cause for the false triggering in the case and some positive common source inductance help to mitigate the crosstalk issue. A packaging layout method is proposed to create the positive common source inductance through layout of control terminals / busbars, and/or the use of control terminal bonded wires at different height.

Exhaust systems can be a source of vibrations that transmit inside the vehicle through the exhaust hangers. These vibrations are caused by engine excitations under acceleration. During the upfront development stage, it is important to predict accurately the forces of the exhaust hangers in order to drive a robust exhaust system design and prevent objectionable noise and vibrations inside the vehicle. This paper describes an FEA-based simulation method to predict the exhaust hanger forces. It demonstrates the effect of temperature on the exhaust dynamic behavior and its importance for an accurate prediction of the exhaust hanger forces.

Self-pierced rivet (SPR) and adhesive are two important joining technologies widely used in automobile industry, and they are often used together to form a hybrid joint. SPR and adhesives can often be used in close proximity in a component, leading to an interaction of the two joints. This interaction can influence the corrosion and noise, vibration and harshness (NVH) characteristics of the structure, as well as its strength and durability. In this paper, the stress distribution in an SPR-adhesive hybrid joint is evaluated by using the finite element method, and then compared with that in an adhesive joint. Results indicate that the stress concentrates at the edge of adhesive layer in hybrid joint and adhesive joint and around the rivet in an SPR joint. The effect of rivet is numerically investigated by either removing the rivet from the hybrid joint or changing the position of the rivet on the overlapping area.

Ultrasonic fatigue tests (testing frequency around 20kHz) have been conducted on A356 aluminum alloys with different copper contents and AS7GU aluminum alloy. Tests were performed in dry air and submerged in water conditions. The effect of copper content was investigated and it was concluded that copper content plays an important role influencing the humidity effect on A356 aluminum alloy ultrasonic fatigue lives. Also, for the same copper content, copper in solute solution or in precipitate have different humidity sensitivities.

The business environment is ever changing, several innovations have allowed companies to transcend borderlines and become global entities. While the opportunities are numerous so are the challenges. In this fiercely competitive global marketplace, success requires companies to pay closer attention to supplier relations. The relationship between an automotive industry and its suppliers is an example of it, so the application of CAE (Computer Aided Engineering) superelement technique may improve, in terms of NVH (Noise, Vibration and Harshness), the vehicle development efficiency, without compromising confidentiality directives. Most of NVH requirements must be tracked through Transfer Functions (TFs) analyses at response points located on the Trimmed-Body Finite Element Model (FEM), as for example: Point Mobility, Vibration Transfer Function (VTF) and Acoustic Transfer Function (ATF).

The unpleasant noise (creak) originated from latch-striker interaction, perceived mainly when the vehicle is submitted to uneven road conditions is generated by stick-slip phenomenon mainly due materials incompatibility of contact surfaces. Generally, eliminate this incompatibility is unfeasible due technical and/or economics constrains; this scenario makes it necessary to act in other fronts to neutralize the effects of that incompatibility. Reduce the coefficient of friction from one of contact surfaces is an alternative that can be easily applied at striker through a thin thickness coating with that property.

During a B-Car durability validation route, it was observed a squeak noise coming from front suspension structure. In the teardown, it was verified metal to metal contact between coil spring and damper spring plate and squeeze-out of spring pad. To reproduce the vehicle failure, it was developed in laboratory a fixture and test to reflect a B-Car McPherson suspension motion, to reproduce the failure and validate a proposal. After root cause understanding, the challenge was to design a new spring pad to avoid squeeze-out keeping the coil spring lower pigtail unchanged. It was tested some prototype parts also in vehicle to approve the design proposal.

The performance of a vehicle’s Automatic Speech Recognition (ASR) system is dependent on the signal to noise ratio (SNR) in the cabin at the time a user voices their command. HVAC noise and environmental noise in particular (like road and wind noise), provide high amplitudes of broadband frequency content that lower the SNR within the vehicle cabin, and work to mask the user’s speech. Managing this noise is a vital key to building a vehicle that meets the customer’s expectations for ASR performance. However, a speech recognition engineer is not likely to be the same person responsible for designing the tires, suspension, air ducts and vents, sound package and exterior body shape that define the amount of noise present in the cabin. If objective relationships are drawn between the vehicle level performance of the ASR system, and the vehicle or system level performance of the individual noise, vibration and harshness (NVH) attributes, a partnership between the groups is brokered.

The design and operation of a vehicle’s heating, ventilation, and air conditioning (HVAC) system has great impact on the performance of the vehicle’s Automatic Speech Recognition (ASR) and Hands-Free Communication (HFC) system. HVAC noise provides high amplitudes of broadband frequency content that affects the signal to noise ratio (SNR) within the vehicle cabin, and works to mask the user’s speech. But what’s less obvious is that when the airflow from the panel vents or defroster openings can be directed toward the vehicle microphone, a mechanical “buffeting” phenomenon occurs on the microphone’s diaphragm that distresses the ASR system beyond its ability to interpret the user’s voice. The airflow velocity can be strong enough that a simple windscreen on the microphone is not enough to eliminate the problem. Minimizing this buffeting effect is a vital key to building a vehicle that meets the customer’s expectations for ASR and HFC performance.

In this paper, a systems engineering approach is explored to evaluate the effect of design parameters that contribute to the performance of the embedded Automatic Speech Recognition (ASR) engine in a vehicle. This includes vehicle designs that influence the presence of environmental and HVAC noise, microphone placement strategy, seat position, and cabin material and geometry. Interactions can be analyzed between these factors and dominant influencers identified. Relationships can then be established between ASR engine performance and attribute performance metrics that quantify the link between the two. This helps aid proper target setting and hardware selection to meet the customer satisfaction goals for both teams.

This paper describes two case studies in which multiple microphone processing (beamforming) and microphone location were evaluated to determine their impact on improving embedded automatic speech recognition (ASR) in a vehicle hands-free environment. While each of these case studies was performed using slightly different evaluation set-ups, some specific and general conclusions can be drawn to help guide engineers in selecting the proper microphone location and configuration in a vehicle for the improvement of ASR. There were some outcomes that were common to both dual microphone solutions. When considering both solutions, neither was equally effective across all background noise sources. Both systems appear to be far more effective for noise conditions in which higher frequency energy is present, such as that due to high levels of wind noise and/or HVAC (heating, ventilation and air conditioning) blower noise.

This paper describes a method to validate in-vehicle speech recognition by combining synthetically mixed speech and noise samples with batch speech recognition. Vehicle cabin noises are prerecorded along with the impulse response from the driver's mouth location to the cabin microphone location. These signals are combined with a catalog of speech utterances to generate a noisy speech corpus. Several factors were examined to measure their relative importance on speech recognition robustness. These include road surface and vehicle speed, climate control blower noise, and driver's seat position. A summary of the main effects from these experiments are provided with the most significant factors coming from climate control noise. Additionally, a Signal to Noise Ratio (SNR) experiment was conducted highlighting the inverse relationship with speech recognition performance.

Vehicle chassis mounted cantilevered components should meet two critical design targets: 1) NVH criterion to avoid resonance with road noise and engine vibration and 2) satisfied durability performance to avoid any incident in structure failure and dysfunction. Generally, two types of testing are performed to validate chassis mounted cantilevered component in the design process: shaker table testing and vehicle proving ground testing. Shaker table testing is a powered vibration endurance test performed with load input summarized from real proving ground data and accurate enough to replicate the physical test. The proving ground test is typically performed at critical milestones with full vehicles. Most tests are simplified lab testing to save cost and effort. CAE procedures that virtually replicate these lab tests is even more helpful in the design verification stages.

The FMEA and DV&PV process of developing automotive products requires identifying and repeatedly testing critical vehicle attributes and their response to noise factors that may impair vehicle function. Ford has developed a new automated scripting tool to streamline in-vehicle robustness testing and produce more accurate and repeatable results. Similar noise factors identified during the FMEA process are grouped together, condensed, and scripts are developed to simulate these noise factors using calibration parameters and vehicle controls. The automated testing tool uses the API of a calibration software tool and a graphical scripting interface to consistently simulate driver inputs with greater precision than a human calibrator and enable more sophisticated controls, which would have previously required experimental software builds. The noise factor scripts are executed with minimal intervention from a human operator, and the collected data is analyzed to determine robustness.

Demand for enhanced infotainment systems with features like navigation, real-time traffic, music streaming service, mirroring and others is increasing, forcing automakers to develop solutions that fulfill customer needs. However, many of those systems are too expensive to be fitted to an entry-level vehicle leaving a gap in the market that fails customer’s expectation. This gap is usually filled by a smartphone which may have all the features the customer wants but in many cases it cannot be properly fitted in the vehicle due to lack of specific storage space. This paper describes how the engineering team developed an innovative, flexible and effective solution that holds a smartphone in an ergonomic location.

Along with the development and marketability of vehicles without an internal combustion engine, electrically heated surfaces within these vehicles are getting more and more important. They tend to have a quicker response while using less energy than a conventional electric heater fan, providing a comfortable temperature feel within the cabin. Due to the big area of heated surface it is important to spread the heating power in a way that different heat conduction effects to underlying materials are considered. In case an accurate sensor feedback of the targeted homogeneous surface temperature cannot be guaranteed, a thermal energy model of the heated system can help to set and maintain a comfortable surface temperature. For a heated steering wheel development project, different models have been created to meet that aim using mechanistic approaches starting with a predominantly first-order dynamics model and ending with a distributed parameter multi-feedback system.