Using the motto “efficient future mobility”,are supporting and shaping the path towards electric mobility with close customer collaboration.These activities are primarily focused on consistently optimizing the internal combustion drivetrain,on hybrid modules and on components and modules for E-Mobility.
A novel approach for the calculation of friction induced vibration is presented and applied to a real life example. The balance equations of continuum mechanics representing the underlying physics are simplified and then solved numerically. First, a linearised model of the example system is built to extract modal parameters such as eigenvalues and eigenvectors. A subset of eigenvectors is then used to calculate the system’s response due to friction related excitation. This non-linear vibration is calculated by utilising an explicit time integration scheme. With the use of a subset of eigenvectors the degree of freedom of the system is reduced drastically, leading to considerable reduction of computational effort. The solution is compared to results from adequate experiments. Although developed in a context of noise calculation in the automotive sector, this work focuses on the calculation of friction induced vibration, rather than on noise prediction. Nevertheless, as an example the resulting noise of the vibrating system is estimated by means of the Equivalent Radiated Power (ERP).
To evaluate the acceptability by elderly drivers of a proactive braking intervention system, we conducted an experiment using an actual vehicle, which could control velocity autonomously, on a test track. After driving the experimental vehicle, the participants evaluated acceptability from various aspects by subjective questionnaires. From the results of 21 elderly drivers, we confirmed the following tendencies: partly negative evaluations for reactive factors, positive evaluations for comprehensive factors, and positive evaluations for total acceptance. In addition, from the results of the trials in which we used head-up display, we confirmed that an information sharing system could improve the evaluations of reactive factors.
This paper proposes a self-localization method for automated vehicles by using traffic signs. The proposed method aims to improve the accuracy of longitudinal self-localization. In order to search for the highest probability position, map matching is performed using predefined digital map data. The images for matching, specifically, (Filtered sign image, Ideal sign image) are made at each position in longitudinal direction. A filtered sign image is extracted from the road forward camera image whereas an ideal sign image is created using the digital map data. The similarity between these two images is then calculated using ZNCC (Zero-means Normalized Cross Correlation). The corresponding posterior probability of the similarity is updated by the BBF (Binary Bayes Filter) and the vehicle position is estimated accordingly. The actual experiments were performed based on two traveling data. The result obtained using the proposed method indicated that the localization accuracy in the longitudinal direction was improved by approximately 15.0% regarding RMS (Root Mean Square) error.
SCR systems are mainly used in exhaust systems as an emission control device for diesel engines with excellent thermal efficiency. In this paper we explored the design of mixing devices which are an important element in the system. The optimum shape for various conditions and designs to disperse ammonia from a urea solution was optimized with CAE and design space exploration, and validated with visualization experiments for correlation.
Vehicles with SAE Level 2 or 3 automation rely on the driver to intervene and resume control when failures occur. In cases which the driver must steer upon regaining control, the initial conditions of the vehicle’s state variables can affect the success of the drivers' recovery. Hence, a model to determine the consequences of these initial states could help identify the requirements of shared control to guarantee a smooth recovery after an automation failure. Such a modeling tool should be simple, such as a two-point visual continuous control model of steering. Data to validate such a model were collected from participants driving in the NADS-1 simulator who were placed in a situation similar to an extreme case of automation failure by drifting their vehicle to a target heading angle and lane deviation. This was done while the drivers were distracted with a secondary task that kept their eyes off the road. The maximum lane deviation reached during recovery shows that the initial heading angle and steering wheel angle strongly affected the maximum lane deviation. Moreover, a slightly modified version of the two-point visual control model was used to simulate the drivers' steering profiles. The model was successful at recreating the participants heading angle and lane deviation profiles but failed to replicate the drivers' steering profile. This simple model of steering control could be used to assess the consequences of a vehicle ceding control at various initial conditions, but is not able to reproduce all aspects of steering control.
This paper describes a motion planning algorithm for unstructured dynamic environments with motion prediction for moving obstacles. The proposed algorithm is composed of the four steps: 1) target motion prediction; 2) drivable area decision 3) local path planning and 4) vehicle control. The target motion prediction is crucial parts for realizing autonomous valet parking system because many vehicles which search available parking lot exist simultaneously. To predict future motion of target, the intention of the target should be inferred first. Interacting multiple model (IMM) filter using two models has been used to infer the intention of the target. Based on the inferred intention, most appropriate model’s results are used as a predicted trajectory of the target vehicle. After that, the drivable area is decided to avoid collision with static obstacles and moving targets using potential filed approach to assessment the risk. In this stage, pre-defined parking lot map which contains boundary of the parking lots and waypoints is used to define initial guess of the drivable area. Inside the drivable area, rapidly-exploring random tree (RRT) generate the desired local path while guaranteeing the real-time performance in dynamic environments. Finally, path tracking controller and speed controller calculate desired steering wheel and longitudinal acceleration input. The proposed motion planning algorithm is validated via MATLAB based computer simulation. Simulation results demonstrate the ability of the proposed motion planning algorithm for unconstructed dynamic environments to plan collision-free path which is appropriate in parking lot situations.
This paper addresses a critical issue of automotive safety. Advanced Driver Assist Systems (ADAS) are getting enormous reputation with the increasing traffic on roads day by day. This paper presents a design of an Automatic Emergency Pullover (AEP) strategy using active safety systems for a semi-autonomous vehicle on a driving simulator. The idea of this system is that a moving vehicle equipped with an AEP system can automatically pull over on the roadside safety shoulder when the driver is considered incapable of driving. AEP requires supporting features such as Lane Keeping Assist (LKA), Blind Spot Monitoring (BSM), Vehicle and Pedestrian Automatic Emergency Braking (AEB), and Adaptive Cruise Control (ACC) for its execution. The design for application of AEP system has been explained along with its algorithm development and component structure. The implementation of AEP system has been explained along with its vehicle behavior and trajectory precision using software tools provided by Realtime Technologies, Inc. All major variables that influence the performance of vehicle after AEP activation, have been observed and remodeled according to control algorithms. The working of AEP system and its vehicle control strategy has been verified with the help of simulation results.
Vehicle-pedestrian crashes are more likely to result in fatalities or severe injuries as compared to vehicle-vehicle crashes. Therefore, various vehicle-pedestrian crash-warning solutions have been proposed. In this report, we first analyze pedestrian-fatality-statistics in the world, Japan, and the US; we then examine various vehicle-pedestrian crash-warning solutions, including three types of communication-solutions that can detect pedestrians in non-line-of-sight: “pedestrians’ communication-modules communicate to vehicles directly”, “vehicles’ modules detect pedestrians’ mobile-phones”, and “vehicles and pedestrians communicate through mobile-network”. Next, we analyze technical challenges in communicationsolutions: channel-congestion, communication-delay, and others. Finally, we conclude this report with approaches to implement communication-solutions for vehicle-pedestrian crash-warnings.
In Nagano prefecture, fatal traffic accidents and fatalities have not decreased for these days compared to the whole of Japan. Especially, the number of fatalities increased in 2016 from the previous year by 76%. Nagano is one of local prefectures, which have mountainous area, cold and snowy district in Japan. It’s sure that a lot of traffic accidents occurred by remarkable local causes. Therefore, it is an imperative issue to analyze these real accident causes. This paper analyzed characteristics of traffic accidents in Nagano using statistical accident data by comparing Nagano with the whole of Japan. The data indicates Nagano has lots of vehicle alone fatal accidents, and accidents in hilly and mountainous area, where lots of roads have up-down slope and curve. Moreover, the cluster analysis using the rate of fatalities or fatal accidents shows that Wakayama, Yamanashi, Nara and Shiga prefecture have same statistical characteristics of traffic accident as Nagano. It is essential approach to analyze the common causes in these local prefectures to reduce fatal accidents in Japan effectively toward zero accidents.
The design of automatic transmissions is a challenging task due to complex power flows and high variability of architectures. To overcome those difficulties a methodology is proposed which uses computational design synthesis to generate transmission designs. The methodology is efficiently dealing with the complexity and variability of transmissions while the engineer is focusing on the application of his engineering knowledge. An analysis of 1022 patented transmissions is shown and highlights the trend of increasing complexity in order to achieve higher capability. The generation of innovative transmission designs is presented producing designs with improved properties.
The development of automated driving technology has been gaining momentum in recent years. Some of the technologies receiving attention involve using a communications system to get information on hazards in blind spots that are hard for the vehicle’s autonomous sensors to detect, or to get advance traffic signal information. Traffic Signal Prediction Systems (TSPS) are one kind of system using such communications technology. Field operation tests were carried out on public roads in 2014-2015to bring these systems closer to practical application. The tests suggested the number of traffic accidents would decline with the implementation of TSPS, since vehicles would come to a “slow stop” more often and encounter the dilemma zone less often. The tests and traffic flow simulation also indicated that this would have little effect on travel time.There was also concern that advising drivers to release the accelerator while the light was still green would increase the incidence of acceleration to try to get through the intersection before the green light ends. As the system was used, however, it was confirmed that the operation decreased. From the questionnaire to those who participated in this tests, this system was evaluated that information supportis easy to understand and is a useful.
With driving parts including a motor equipped inside each wheel, in-wheel motor system drives wheels directly. If the motor is combined with CTBA, the drive system and the suspension system are modularized in a simple structure, expanding inside space and improving cost competitiveness. Moreover, as a controller of driving power and braking force of the motor, it also enhances ride quality and handling by controlling the pitch and yaw of the vehicle. However, in-wheel system directly related to the sash is disadvantageous to vibration isolation of the motor/reduction gear. The purpose of this research is to identify the causes of 1st. order vibration in vehicles with motor integral CTBA and suggest countermeasures to this problem.
Within the FVV-Project Piston Ring Oil Transport a novel research engine was developed for the investigation of the lubricating oil management in the piston assembly. The various measurement techniques are applied for detailed studies of the lubricating oil film thickness, oil transport, and the complex movements, and pressure conditions at the system piston assembly.
Due to the low energy density of electrochemical battery in Electric Vehicles (EVs), the driving range per charge has been limited. However, the widely adopted single reduction gear in EVs typically do not achieve the diverse range of functional needs. Consequently, multi-speed EV powertrains have been compared and investigated for these applications. Through the optimizing of gear ratios, a more diverse range of functional needs can be realized without increasing the practical size of the electric motor. This paper studies the performance improvements realized through utilization of 2-4 speeds and continuously variable transmission. Results demonstrate that there can be significant benefits attained for both small and large passenger vehicles.
To continue efforts towards improving air quality and achieving Read World Driving emissions targets, it is accepted thatLight Duty Diesel powertrains have to maximize the NOx reduction performance of exhaust aftertreatment systems. Therefore Ricardo have continued to study the optimum configurations and thermal management techniques to improve conversion efficiency across all driving styles. The paper will consider what aftertreatment types, positions, and heating methods can achieve these goals towards post Euro 6 emissions levels, by assessing conversion efficiency profiles over WLTP and RDE cycles.
We propose a method to predict trajectories of surrounding vehicles considering individual drivingcharacteristics. Trajectory prediction of surrounding vehicles is attracting a lot of attention now, and it is expected to apply to advanced driver assistance systems. However, previous methods perform the trajectory prediction based on common driving patterns even though each driver shows a different driving characteristic. The proposed method focuses on the following behavior behind the preceding vehicle and estimates a driving characteristic of each driver using machine learning techniques. Based on the estimation result, the proposed method adjusts the prediction model and appropriately generates a trajectory. As the result, the performance of trajectory prediction can be dramatically improved.
Lane departures can have serious consequences when resulting in run-off-road and oncoming crashes and effective countermeasures are of utmost importance. The objective of this study was to evaluate the real-world crash avoidance effectiveness of a Lane Departure Warning (LDW) crash avoidance system, introduced as optional mounted equipment in Volvo car models in 2008. Situations addressed by the LDW system—single-vehicle run-off-road and oncoming crashes in which the driver unintentionally leaves the lane without loss of control—were identified in insurance claims data. To evaluate the crash avoidance effect, crash rates were calculated and compared for vehicles with and without LDW. The rate of run-offroad crashes without traction loss was reduced by 30% if the vehicle had LDW (RD = 0.20 , 80% CI [0.03, 0.37]). There were not enough oncoming crashes to evaluate them statistically. The analysis revealed that the system has a large crash avoidance effect in real-world traffic; and the findings are promising for further refinement of these technologies, which target the avoidance of run-off-road and oncoming crashes.
In the development phase a typical means of cost saving is the replacement of a sensor with a model. A model-based methodology combined with statistical approaches is presented, enabling a holistic view on the cost and legal consequences of such a decision. It considers production tolerances, environmental conditions and their joint effect on component aging. Additionally, the effect of methodical inaccuracies on the results is reflected by confidence levels. Finally, by means of a use case, the methodology is applied to assess the exchange of a mass flow sensor by a corresponding model in terms of TCO and legal conformity.
Piston to liner friction is responsible for a significant part (up to 50%) of total engine friction losses. Engine manufacturers use liner offset designs to address this issue and potentially reduce friction losses as is to be expected from theoretical considerations. A “floating liner” single cylinder engine was used to directly measure the effect of such liner offset design on the friction losses. Results show benefits to be gained at moderate speeds where cylinder pressure effects are the main drivers of piston to liner contact forces. At high engine speed this trend reverses due to piston inertia effects.
A new real-time pressure loss compensation method was developed for hydrogen refueling stations to increase fuel cell vehicle driving ranges. Pressure loss coefficient measurement every refueling enabled to distinguish the conditions of each vehicle and the station. A time-lag pressure loss measuring method was utilized to accurately get the pressure loss without the vehicle’s data. The vehicle tank pressure was accurately estimated only from the station’s measurement data. As a result, the vehicle’s SOC was enhanced by an average of 4.6%
Cardiovascular diseases are highly prevalent and fatal medical conditions cause many adult deaths annually. The occurrence of a debilitating cardiac condition while driving could suddenly render a driver unable to safely operate a vehicle, including bringing a vehicle to a stop in order to request medical assistance. Currently, many people are at risk of suffering from conditions such as a heart attack or arrhythmia. We conduct a feasibility study to determine the practicality of developing an in-vehicle severe cardiac event detection system, integrated with a driver monitoring system, to detect or predict these events. We provide background information related to the primary diagnostic criteria and evaluation of the Electrocardiogram (ECG). A preliminary noise analysis is conducted to compare the ECG noise of in-vehicle and in-lab signals. Ultimately, we determine that developing a driver monitoring system capable of determining the driver’s cardiac health is completely feasible.
This paper presents a technique of automatic 3D pavement defects detection using both the two-dimensional (2D) and three-dimensional (3D) information from the images captured at high speed. Scaled 3D points reconstructed from Structure from Motion algorithm are first used to detect the defect regions based on the 3D information. A mismatched points rejection method then eliminates incorrectly matched points and reconstructs a final 3D road surface. The proposed technique uses both 3D and 2D information for the defects detection where the characteristics of defect regions in 2D images together with the 3D information from the 3D reconstruction detect the defect region. The capability of the proposed technique was first investigated through parameters studies. Quantitative analyses have shown the accuracy, precision, and recall rate of the proposed technique are all above 90%. The result demonstrates the potential of the proposed technique for the automatic detection of 3D pavement defects.
We explore a feasibility of reducing the time lag between the instant when a driver decides to apply brakes and the instant the car reaches its maximum deceleration in emergency braking situations. The former event is manifested by the energetic lifting of the accelerator pedal, while the latter – by pressing the brake pedal to its maximum position. The time lag between these two events is a personal trait, and, in most cases, it is about few hundreds milliseconds. Depending on the speed, the considered time lag corresponds to several meters of distance traveled by car. By reducing this time lag, we intend to reduce the overall braking distance of the car in emergency braking. As the first step in our research towards the reduction of the time lag we consider investigating the cause and effect relationship (if any) between the event of energetic lifting the accelerator pedal and pressing the brake pedal to its maximum position. Presence of such a relationship would indicate that, in principle, the imminent braking could be predicted from the movement of the accelerator pedal, and consequently – an automated proactive braking could be applied well before the driver would have been able to apply the brakes.
Overall efficiency of internal combustion engines are heavily depended on intake air temperature which is directly related to the heat transfer inside an intake system. Previously, authors developed an equation by using port model setup to calculate Nusselt number with introduction of Graetz and Strouhal numbers. This study modified the port model equation to improve its accuracy in a real engine experimental setup. Predicted intake air temperature was compared to the measured data with a maximum error of 5.6%. Additionally, 100 K of temperature difference was found between the boost pressure values of 944hPa and 678hPa from 1-D engine simulation results.