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Running gear
Published in Andrew Livesey, Practical Motorsport Engineering, 2019
Wheelbase (WB) – is measured from the centre of the front axle (imaginary) to the centre of the rear axle. The overall length (OL) is measured from front bumper to rear bumper. Both the wheelbase and the ratio of the wheelbase to the overall length (k1) k1 = WB/OL are important variables in suspension design. A long wheelbase relative to the overall length of the vehicle allows for the accommodation of passengers between the axles, so the floor can be flat in the foot well and the seat cushion height has less special constraints. It reduces the affect of load positioning in the vehicle; this includes the position of the engine and gearbox. It reduces the tendency to pitching, especially on undulating country roads, which in turn allows the use of softer springs that tend to give passengers a more comfortable ride. With the reduced overhang there is less polar inertia, which improves the swerveability of the vehicle. The length of the wheelbase affects the turning circle for any given input of steering angle. American car companies have set ratios for wheelbase and overall length; this is to give a particular aesthetic to their full size cars – for example the Lincoln. On the compacts and sub-compacts (ordinary European-style cars) this does not apply.
Evaluation Studies
Published in Vivek D. Bhise, Automotive Product Development, 2017
The vehicle package is generally developed by package engineers assigned to the vehicle program along with the inputs from design (styling), engineering, and marketing professionals. However, it is generally desirable to get an independent confirmation on the vehicle package by conducting a market research clinic in which a representative group of prospective owners are asked to evaluate the overall vehicle package. A full-size interior buck of the vehicle with the passenger compartment and trunk/cargo area is created. The buck includes all the interior surfaces (i.e., instrument panel, door trim and roof-liner surfaces) with storage areas and major vehicle controls (i.e., pedals and steering column with the steering wheel) and seats.
Drive for Free
Published in Alden M. Hathaway, Tripp Hathaway, Energy Independence: The Individual Pursuit of Energy Freedom, 2022
Alden M. Hathaway, Tripp Hathaway
If you can go 52 miles on a single charge for $1.32 with a Honda Clarity, what would that cost in your current vehicle? Let’s compare the cost to a similar full-size sedan like the 2020 Honda Accord with a 2.0 L, 4 cylinder engine. With a combined fuel economy of 27 MPG, it would cost you $5.78 to drive the Accord 52 miles with gas at $3.00 per gallon. A 52 mile round-trip commute Monday through Friday in this scenario would save you almost a hundred dollars per month.
Effects of mixed policies on the cooperative and noncooperative strategies of auto manufacturers and charging infrastructure operators considering consumer preferences
Published in Energy Sources, Part B: Economics, Planning, and Policy, 2023
First, different purchasing groups have different preferences of vehicles (Xiong et al. 2023). Consumers of different genders, ages, education levels, or income levels have different preferences for body types (Liao et al. 2019), purchase prices (Carley et al. 2013), charging time (Jang and Choi 2021), driving range (Franke and Krems 2013; Xiong et al. 2023), emission reduction of electric vehicles (Peng, Li, and Yu 2021). D, Mohamed, and R (2017) used the multivariate analysis of variance (MANOVA) model to analyze consumer preferences for vehicle body types (economy, intermediate, full-size sedan, luxury, minivan, sport utility, and pickup). Xiong et al. (2023) built the random coefficient logit model (BLP) to analyze the consumer’s preferences for EVs. The result shows that consumers’ preferences for EVs are significantly heterogeneous in cities at different development stages. Peng, Li, and Yu (2021) suggested that long driving ranges and the environment-friendliness of electric vehicles are more popular among consumers. These articles analyze the preference heterogeneity of consumers for electric vehicles. This article also considers the effects of consumers’ green preferences on optimal decisions.
Multi-sensor driver monitoring for drowsiness prediction
Published in Traffic Injury Prevention, 2023
Chris Schwarz, John Gaspar, Reza Yousefian
Data were collected using the high-fidelity full-motion NADS-1 simulator at the National Advanced Driving Simulator at the University of Iowa. The simulator consists of a 24-foot diameter dome enclosing a full-size 2014 Toyota Camry sedan with active steering and pedal feedback. A 13-degree of freedom motion system provides participants accurate acceleration, braking, and steering cues they expect from driving (see Figure 1, left). Sixteen high-definition (1920 × 1200) LED (light emitting diode) projectors display seamless imagery on the interior walls of the dome with a 360-degree horizontal field of view. The data sampling rate was 240 Hz. Aisin Technical Center of America (from Aisin Group) supplied two separate production-type Driver Monitoring System (DMS) units which were integrated into the Camry cab (see Figure 1, right). One was installed on the steering column, while the other was mounted on the dash above the center console. In this work only data from the steering column unit was used. Physiological data were collected using an Empatica E4 wristband, a photoplethysmography sensor that optically measures blood volume pulse (BVP). In addition to collecting physiological data during the drive from the E4, breathing and heartrate were also collected with a non-contact, millimeter-wave radar.
Reduced Pressure Effect On The Flame Length Of Elevated N-Heptane Fires In An Aircraft Cargo Compartment
Published in Combustion Science and Technology, 2022
Jie Wang, Gongyousheng Cui, Kaihua Lu, Xuepeng Jiang
As shown in Figure 1, experiments were carried out on a rectangular cabin with curved sides, which was similar to the actual cargo bay of Boeing 737–700 forward cargo compartment. The cabin is made of 8 mm thick stainless steel with an internal dimension of 4.67 m long and 1.12 m high, and the top and bottom of the cabin are 3 m and 1.22 m wide. The full-size simulated aircraft cargo is composed of cargo compartment, pressure control system, and other auxiliary systems. The full-size simulated aircraft cargo is equipped with an extraction hole connected to a vacuum pump. Before conducting a fire experiment in reduced pressure. the pressure control system is activated and the vacuum pump pumps the cargo compartment to a set low-pressure environment at a set rate. During the experiment, if the pressure exceeds or falls below 3% of the set pressure, it will automatically make up or pump the air. The pressures in the simulated aircraft cargo range from 60 kPa to 100 kPa and can be controlled by a control system with a vacuum pump. In this experiment, with reference to the pressure in the cargo hold of a real aircraft from sea level to cruising altitude (approx. 10,000 m), we set the ambient pressure inside the compartment at 70 kPa, 80 kPa, 90 kPa, and 100 kPa. For fire test, the compartment pressure should be kept at the specified value during the whole test, and the measurement uncertainty should be ±2%.