Browse Topic: Road tests

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NVH Design and Refinement of Dedicated Hybrid Engine on Range-Extended Electric Vehicle2026-01-06886/20/2026
Simplicity and electrification of the propulsion system are one of the most important trends in vehicle development and integration process. The complexity of NVH (Noise, Vibration and Harshness) design and refinement is the core challenge to this process. Customers’ expectations of an unnoticeable engine during driving make this challenge more critical [1]. Apart from the overall sound pressure level, the sound quality is even more important due to the lack of noise masking effects [2]. Therefore, the development team has reached an internal consensus that NVH attributes are the top priority in engine development. This paper describes the NVH development process of a dedicated hybrid engine for the range extender electric vehicle (REEV) application, beginning with an introduction to REEV system as well as the operating condition data of long-distance road tests. Based on the road test data, the engine technical specification is defined accordingly and broken down into design targets for all individual components. Subsequently the design target is finally achieved through the definition of engine architecture, hardware selection, and individual component simulation and optimization. With regard to the NVH refinement, the NVH issues such as global crankshaft vibration, start impacts, high-pressure fuel system ticking, and acoustic encapsulations studies are discussed. Finally, the appropriate optimization proposals are summarized and the bench test results are presented.
Wang, Hao, Zhang, Guiqiang
Understanding and Modeling Effectiveness of Predictive Risk Notifications for Early Assistance for Safe Driving: A Public Road Testing Study09-14-01-00265/4/2026
While an enlarged lead time from risk notifications to collisions is widely acknowledged to facilitate safe driving, it remains challenging to effectively notify drivers of invisible risks and non-apparent risks coming from uncertain behaviors on the part of road users. The current study examined whether verbal notifications are able to assist early awareness of predictive risks. We also attempted to identify human and environmental factors that could possibly improve the effectiveness of predictive risk information. Twenty-eight licensed drivers participated in a public road test conducted in two different urban areas on 3 days. They drove predefined courses on which potential risk locations were identified prior to the test, using a sport utility vehicle equipped with an automatic verbal notification system triggered based on the distance to the potential risk locations. After passing through the locations each time, the participants were instructed to verbally evaluate the shift in awareness provided by the notification and the usefulness of the assistance. After the driving test was completed, we acquired a subjective evaluation on annoyance acceptability and a self-report of participants’ road usage frequency at notified locations in daily life, as well as questionnaires on their driving style and workload sensitivity. We found that the effectiveness of verbal notifications increased by conveying uncertainty risks at visible locations and by using interrogative sentences or expressions of risk target perspective, although it decreased as a function of age. Our model showed strong performance in predicting positive ratings for the notifications, but this was not the case for negative ratings. We identified individual characteristics and the risk factor of uncertainty as important features in our model. In conclusion, the findings provide an important reference for understanding the early notification of predictive risk and constructing a numerical model for the implementation of assistance systems in vehicles and nomadic devices.
Maruyama, Masaki, Koyama, Keiichiro, Ezaki, Toru, Sakamoto, Junichi, Sawada, Yuta, Matsuoka, Takahiro
Truck and Bus Coastdown ProcedureJ2978_202604 (Current)4/28/2026
This document describes a rigorous engineering test procedure that utilizes industry-accepted data collection and statistical analysis methods to determine the road load and to estimate the aerodynamic drag area of trucks and buses weighing more than 10000 pounds. The test procedure may be conducted on a test track or on a public road under controlled conditions and supported by extensive data collection and data analysis constraints. The estimated aerodynamic-drag-area result represents a single-speed and single-yaw-angle condition. Test results that do not rigorously follow the method described herein shall not be represented as an SAE J2978 result.
Truck and Bus Aerodynamics and Fuel Economy Committee
Vehicle Deceleration Levels during Wet-to-Dry Transitions on an Asphalt Surface with a High Proportion of Aggregate2026-01-05424/7/2026
The braking performance of a vehicle at varying levels of road wetness is an important factor in collision reconstruction. Here we quantify the deceleration levels of two modern vehicles equipped with antilock brake systems (ABS) on a wetted asphalt surface with a high proportion of exposed, large-sized aggregates as the road naturally dried over time. We also compare our current results to prior tests on asphalt with a small proportion of small-sized aggregate. Two ABS-equipped vehicles were maximally braked on an asphalt road surface as the road naturally transitioned from a saturated wet state to a completely dry state. Road wetness was visually categorized from photographs taken during testing. Overall, we found that deceleration levels on wet asphalt were significantly less than deceleration levels on dry asphalt (average dry: 0.902g and 0.962g; average wet: 0.787g and 0.818g for the two vehicles). Within the wetness categories we used, there was either no significant difference or only a small significant difference between the three wettest categories (road surface >75% wet, 100% wet with a matte surface, and saturated with a glossy surface). Similarly, there were no significant differences between the two driest conditions (road surface <25% wet and completely dry). This pattern of findings is similar to our prior tests, although the absolute deceleration levels in the current study were 0.028g lower on dry asphalt and 0.076g lower on wet asphalt than in our prior study on asphalt with a lower proportion of smaller-sized aggregate but a similar mean texture depth. These findings provide two important insights: first, the current data support our prior proposition of a readily identifiable boundary in ABS deceleration levels between dry and wet road surfaces, and second, ABS deceleration levels measured using the current test methods may be more sensitive to changes in road surface friction than the standardized measure of road surface macrotexture we used here.
Ahrens, Matthew, Arnold, Nikolas, Miller, Ian, Siegmund, Gunter P.
Navigation Integrated End-To-End Path Planning Development and Vehicle Testing2026-01-00324/7/2026
In order to achieve fully autonomous driving, point to point autonomous navigation is the most important task. Most existing end-to-end models output a short-horizon path which makes the decision process hard to interpret and unreliable at intersections and complex driving scenarios. In this research, we build a navigation-integrated end-to-end path planner on top of an openpilot open source model. We created a navigation branch that encodes route polyline geometry, distance-to-next-maneuver, and high-level instructions and combines with path plan branch using residual blocks and feed-forward layers. By adding minimal parameters, new model keeps the original openpilot tasks unchanged and have the path output based on the navigation information. The model is trained on diverse urban scenes’ intersections, and it shows improved route performance in vehicle testing. The proposed model is validated in a Comma 3x device installed on a 2025 Nissan Leaf test vehicle. The road test results show the proposed algorithm shows less path planning error than the stock openpilot end to end model when evaluated against the human driver. This proposed path planning model can be adapted to different type of vehicles for the point to point navigation task.
Wang, Hanchen, Li, Taozhe, Hajnorouzali, Yasaman, Burch, Collin, li, Victoria, Tan, Lin, Arjmanzdadeh, Ziba, Xu, Bin
Development of a Tire Blowout Experimental Platform for Dynamics and Control Validation2026-01-02024/7/2026
Tires are critical to vehicle dynamics, transmitting traction, braking, and cornering forces to the road. A tire blowout, the sudden and rapid loss of inflation pressure due to puncture or structural failure, can cause severe instability, rollover, or collisions. Understanding vehicle response during blowout events is essential for developing robust safety systems and control strategies. Earlier developed simulation models are used to study and understand vehicle behavior during blowouts, but there is a lack of on-road testing platforms to validate these models experimentally. In this paper, an experimental platform integrating a tire blowout device and an instrumentation system has been developed to address this gap. The blowout device consists of multiple solenoid valves mounted on the wheel surface and powered by a 12V power supply. All valves can be triggered at the same time using an RF remote, producing rapid and synchronized deflation. As an extension of this implementation, an Arduino-based actuation system is being developed for individual valve actuation and custom deflation profiles. The instrumentation system includes GNSS, IMU, and CAN-based data acquisition for vehicle dynamic variables. Furthermore, outriggers will be installed on the vehicle to ensure safety during testing. Unlike prior devices that use single valves with external pneumatic hoses and laboratory-only operation, the proposed platform is compact, lightweight, and field-deployable due to its integration of multi-valve actuation, custom deflation control, outrigger-based safety measures, and instrumentation. The developed platform enables safe, repeatable, and full-scale on-road blowout testing within required timeframes, providing a novel framework that bridges simulation and real-world validation.
Kanthala, Maha Vishnu Vardhan Reddy, Krishnakumar, Ashwin, Lin, Wen-Chiao, Chen, Yan
MBSE-Driven XIL Workflow for Energy Evaluation of Automated Vehicles: From Simulation to VIL Testing2026-01-02894/7/2026
With the increasing market penetration of automated vehicles, there is a critical need for credible and repeatable methods to quantify their energy impacts. This paper presents a Model-Based Systems Engineering (MBSE)-driven Anything-in-the-Loop (XIL) methodology for quantifying the powertrain energy consumption and potential savings from various controls for automated vehicles in realistic road scenarios while preserving high-fidelity powertrain behavior. The novelty of this approach lies in its use of a unified MBSE backbone (AMBER: Argonne National Laboratory’s [Argonne’s] MBSE-centric platform for transportation energy analysis) to automate the seamless and traceable progression from pure simulation to Vehicle-in-the-Loop (VIL) testing. This work utilizes Argonne's multi-vehicle simulation tool, RoadRunner, which automatically constructs closed-loop road scenarios (road geometry, vehicle sensors, other vehicles, and traffic controls) and connects them to Argonne’s validated, high-fidelity vehicle and powertrain models in Autonomie. The MBSE backbone in AMBER organizes requirements, interfaces, plant and controller models, and test scenarios into a single set of models that is maintained across pure simulation, Software-in-the-Loop (SIL), Processor-in-the-Loop (PIL), and VIL stages. Each stage has a clear role: simulation enables rapid development and validation of advanced models or controls across a large number of scenarios; SIL supports standalone algorithm verification and scenario down-selection; PIL validates real-time execution, inputs/outputs, and timing on the target processor; and VIL provides closed-loop evaluation with a real vehicle under controlled laboratory conditions. AMBER’s automated build and configuration enable rapid retargeting across platforms and repeatable scenario reproduction, making validation fast and cost-effective. To demonstrate its practical application, the workflow is used to validate the functionality and quantify the energy savings of an eco-driving control against a calibrated human driver model. Experiments show strong repeatability and consistent energy gains for the eco-driving strategy while preserving trip time, yielding average energy savings of 7.8% across the evaluated scenarios. Overall, the MBSE-guided XIL workflow shortens development time and reduces test cost by limiting on-road testing and lowering integration risk before track evaluation, while producing credible, closed-loop energy assessments traceable from requirements to test evidence.
Jeong, Jongryeol, Sharer, Phillip, Di Russo, Miriam, Das, Debashis, Zhang, Yaozhong, Karbowski, Dominik
Camera Monitor System Soiling Correlation for a Class-8 Truck Using Lattice Boltzmann Method2026-01-05964/7/2026
As Camera Monitoring Systems (CMS) become an integrated part of the driving experience for current automotive and heavy vehicles, keeping the CMS clean from water, dirt, sand, snow and ice is a main focus of the design process in order to avoid safety issues due to obscured visibility. On-road soiling prevention becomes an important feature when designing the camera and sensor systems. Computational Fluid Dynamics (CFD) analysis can be used to facilitate the design process, to provide important information of the cause of the problems and design mitigation mechanism to prevent the visibility issues. Most of existing work focusses on automotive applications. This paper is targeted for heavy vehicle application. Road tests were performed in Alaska by the testing department. Results from the road test were compared to CFD simulation. This comparison showed a good agreement between CFD and road testing, based on the qualitative soiling deposition patterns, rivulet formation and dispersed wake-based deposition in the sensor regions.
He, Wei, Dasarathan, Devaraj, Linden, Tom, Park, Jeongbin
A Cloud-Vehicle Integrated Closed-Loop Testing Framework for Intelligent Chassis2026-01-00514/7/2026
Vehicle system testing serves as a critical phase in obtaining road certification for prototype vehicles. While direct road testing with physical vehicles yields the most authentic data, this approach entails significant costs, challenges in reproducing extreme scenarios, and inherent safety risks. In contrast, virtual vehicle-based testing technologies represent advanced simulation methodologies for enhancing development efficiency and quality, effectively mitigating risks associated with complex real-world operating conditions and hazardous physical testing. However, virtual vehicle models often rely on idealized parameters, limiting their ability to reflect real-world dynamics and resulting in lower credibility of test outcomes. Furthermore, as evidenced in current mainstream virtual testing software, environmental simulations predominantly remain confined to the visual domain, with limited direct interaction between dynamic environmental changes and virtual vehicle responses. To address these limitations, this study proposes a novel testing framework leveraging vehicle-cloud integration technology, which combines the authenticity of physical testing with the flexibility of virtual simulation. The proposed system is validated through an AEB (Automatic Emergency Braking) function activation test. Experimental results demonstrate real-time data interoperability between physical and virtual vehicles, achieving a 89% accuracy rate in synchronizing virtual scenario velocities with real-world speeds. This approach enables safe and efficient preliminary testing, providing robust data support for subsequent physical validation and significantly lowers the overall testing cycle.
Liao, Yinsheng, Cheng, Qing Hua, Qu, Wenying, Wang, Zhenfeng, Wu, Yan, He, Chengkun, Zhang, Junzhi, Lu, Yukun
Embedded Real-Time Control of a Distributed Trailer Propulsion System with Regenerative Braking for Net Neutral Load Towing2026-01-00654/7/2026
Towing imposes substantial efficiency penalties on both battery-electric vehicles (BEVs) and internal combustion engine (ICE) vehicles, reducing range by 30-50%. This paper presents a proof-of-concept embedded control architecture for distributed trailer propulsion that actively regulates drawbar force to reduce towing loads. Unlike proprietary e-trailer systems requiring specialized hardware, the proposed implementation demonstrates feasibility using commercial off-the-shelf (COTS) components and open-source software. The distributed architecture employs dual Raspberry Pi 4B single-board computers communicating via ROS 2 at 20 Hz. The trailer-mounted controller executes a Simulink-generated control node coordinating load cell acquisition (HX711 ADC), motor CAN bus telemetry, and throttle commands to a 5 kW BLDC traction motor powered by a 5 kWh LiFePO4 battery pack. A vehicle-mounted controller logs OBD-II/CAN validation data. The control pipeline implements cascaded EWMA/Hampel digital filtering with intentional phase lag for hitch-force regulation. The system was validated through on-road testing with an ICE towing vehicle pulling a 1,000-lb trailer over standardized 2.1 km segments following SAE J1321 Type II procedures. Preliminary trials demonstrated stable control performance with drawbar force regulation with no oscillatory behavior. Fuel consumption measurements showed promising improvements (9.4% lower fuel consumption in assisted vs. baseline conditions), though limited sample size precludes definitive causal claims. The primary contribution is establishing technical feasibility of cost-effective COTS implementation (USD 5,000 hardware cost) for trailer propulsion control, providing a foundation for expanded validation studies and commercial deployment pathways.
Joshi, Gaurav, Adelman, Ian, Liu, Jun, Donnaway, Ruthie
BEV Incremental CO 2 Emissions in a Ranked Order Electric Grid2026-01-04244/7/2026
Battery Electric Vehicles (BEV) have been sold as ‘Zero Emissions Vehicles’ (ZEV) by governments to reduce transportation CO2. While they are not ZEV because they run on grid electricity, they could be ‘effectively ZEV’ if the incremental CO2 is ‘very small’. At the national level, this is estimated using following metrics: (1) Internal Combustion Engine Vehicle (ICEV) fuel consumption, from the total US gasoline consumption divided by the total fleet miles driven, 25 mpg or 350 g CO2/mi, (2) Strong Hybrid Electric Vehicles (HEV) about one third less, 240 g CO2/mi. (3) BEV energy consumption, using data from systematic on-road testing of a wide range of vehicles, estimated at 40 kWh/100 mi for a US sales mix. (4) Electricity marginal CO2: in a ranked order grid, zero-CO2 sources are prioritized and supplemented by fossil sources. IEA hourly data show that the US 48 contiguous states are self-contained, with zero-CO2 sources providing a third of total demand. The response to hourly demand changes comes largely from natural gas and coal power stations, with EPA data showing a combined marginal CO2 of 600 g CO2/kWh. On replacing an ICEV by a BEV, the reduction in gasoline use, - 350 g CO2/mi, is offset to two thirds by higher electricity consumption, 40 x 600 / 100 = + 240 g CO2/mi. BEV marginal CO2 is therefore similar to HEV, and not ‘much smaller’ than ICEV. This is because HEV engines and fossil power stations have similar efficiency and similar fuel CO2 intensity.
Phlips, Patrick
Collision Avoidance Testing of the Waymo Automated Driving System2026-01-05194/7/2026
This paper describes Waymo's Collision Avoidance Testing (CAT) methodology: a scenario-based testing method that evaluates the safety of the Waymo Driver Automated Driving Systems' (ADS) intended functionality in conflict situations initiated by other road users that require urgent evasive maneuvers. Because SAE Level 4 ADS are responsible for the dynamic driving task (DDT), when engaged, without immediate human intervention, evaluating a Level 4 ADS using scenario-based testing is difficult due to the potentially infinite number of operational scenarios in which hazardous situations may unfold. To that end, in this paper we first describe the safety test objectives for the CAT methodology, including the collision and serious injury metrics and the reference behavior model representing a non-impaired eyes on conflict human driver used to form an acceptance criterion. Afterward, we introduce the process for identifying potentially hazardous situations from a combination of human data, ADS testing data, and expert knowledge about the product design and associated Operational Design Domain (ODD). The test allocation and execution strategy is presented next, which exclusively utilize simulations constructed from sensor data collected on a test track, real-world driving, or from simulated sensor data. The paper concludes with the presentation of results from applying CAT to the fully autonomous ride-hailing service that Waymo operates in San Francisco, California and Phoenix, Arizona. The iterative nature of scenario identification, combined with over ten years of experience of on-road testing, results in a scenario database that converges to a representative set of responder role scenarios for a given ODD. Using Waymo's virtual test platform, which is calibrated to data collected as part of many years of ADS development, the CAT methodology provides a robust and scalable safety evaluation.
Kusano, Kristofer, Beatty, Kurt, Schnelle, Scott, Favaro, Francesca, Crary, Cam, Victor, Trent
Eco-Driving Control for Electric Vehicles with Multi-Speed Transmission: Optimizing Vehicle Speed and Powertrain Operation in Dynamic Environments12-09-03-00212/28/2026
This article presents an eco-driving algorithm for electric vehicles featuring multi-speed transmissions. The proposed controller is formulated as a co-optimization problem, simultaneously optimizing both vehicle longitudinal speed and powertrain operation to maximize energy efficiency. Constraints derived from a connected vehicle–based traffic prediction algorithm are used to ensure traffic safety and smooth traffic flow in dynamic environments with multiple signalized intersections and mixed traffic. By simplifying the complex, nonlinear mixed-integer problem, the proposed controller achieves computational efficiency, enabling real-time implementation. To evaluate its performance, traffic scenarios from both Simulation of Urban MObility (SUMO) and real-world road tests are employed. The results demonstrate a notable reduction in energy consumption by up to 11.36% over an 18 km drive.
He, Suiyi, Sun, Zongxuan
Parameterizing External Factors Influencing E-Motor Consumption2026-26-01751/16/2026
In recent times, a standard driving cycle is an excellent way to measure the electric range of EVs. This process is standardized and repeatable; however, it has some drawbacks, such as low active functions being tested in a controlled environment. This sometimes causes huge variations in the range between driving cycles and actual on-road tests. This problem of variation can be solved by on-road testing and testing a vehicle for customer-based velocity cycles. On-road measurement may be high on active functions while testing, which may give an exact idea of real-world consumption, but the repeatability of these test procedures is low due to excessive randomness. The repeatability of these cycles is low due to external factors acting on the vehicle during on-road testing, such as ambient temperature, driver behavior, traffic, terrain, altitude, and load conditions. No two measurements can have the same consumption, even if they are done on the same road with the same vehicle, due to the influence of the above-mentioned external factors. The current paper will portray a machine learning-based methodology to parameterize the external factors affecting e-motor consumption. By parameterizing these factors, on-road test results are normalized and further used for comparative studies. The paper also takes us through the process of data collection for this study, the parameterization process of external factors using ML models, for different driving scenarios and ambient temperature ranges. The ML models are developed in a MATLAB environment and can be reproduced in any other tool. Merits and demerits of each ML model are discussed along with ways and means to mitigate each external factor, which will make the testing procedure more robust and reliable. Thus, it helps in making automobiles more energy efficient.
Kelkar, Kshitij, Kanakannavar, Rohit
Virtual Validation of ADAS Algorithms Using Driver-in-the-Loop Simulation2026-26-00501/16/2026
Driver-in-the-Loop (DIL) simulators have become crucial tools across automotive, aerospace, and maritime industries in enabling the evaluation of design concepts, testing of critical scenarios and provision of effective training in virtual environments. With the diverse applications of DIL simulators highlighting their significance in vehicle dynamics assessment, Advanced Driver Assistance Systems (ADAS) and autonomous vehicle development, testing of complex control systems is crucial for vehicle safety. By examining the current landscape of DIL simulator use cases, this paper critically focuses on Virtual Validation of ADAS algorithms by testing of repeatable scenarios and effect on driver response time through virtual stimuli of acoustic and optical warnings generated during simulation. To receive appropriate feedback from the driver, industrial grade actuators were integrated with a real-time controller, a high-performance workstation and simulation software called Virtual Test Drive (VTD). By developing an integrated solution for acquiring driver response, creation of scenarios and evaluation of control systems, this paper focuses on virtual validation of systems in a time saving and cost-effective manner.
Sharma, Chinmaya, Bhagat, Ajinkya, Kale, Jyoti Ganesh, Karle, Ujjwala
A Scientific Approach to Identify the Source of Intermittent Steering Rattle Noise and Implementing the Design Solutions2026-26-03461/16/2026
Body-on-frame vehicles are well-regarded for their durability and off-road capabilities, but their structural design often makes them more vulnerable to noise, vibration, and harshness (NVH) issues. Vibrations originating from uneven roads are transmitted through the suspension and steering assemblies, sometimes resulting in rattles or other disturbances. These vibrations can be amplified by the inherent flexibility in the body-to-frame mounting system. In such vehicles, the steering system plays a critical role in driver comfort and is highly sensitive to vibrational inputs from the road surface, especially on coarse or uneven terrain. Occasionally, these inputs result in subtle rattle noises that are perceptible only to the driver and may not be detected under controlled testing environments. This poses a challenge for engineers trying to isolate and resolve such intermittent NVH phenomena. Identifying the source requires a combination of real-world driving evaluations, structural analysis, and vibration measurement techniques. This paper presents a case study of an intermittent steering-related rattle noise in a body-on-frame D-SUV with a column EPS steering system. A systematic investigation using on-road testing and accelerometer-based diagnostics was conducted. Through targeted design enhancements focused on improving system stiffness and connection integrity, the issue was resolved effectively. The approach outlined offers a replicable methodology for diagnosing and mitigating similar NVH concerns in other vehicle platforms, thereby contributing to improved driver comfort and product refinement.
Ramesh Chand, Karan Kumar, Gopinathan, Haridoss, Kabdal, Amit
Advancing Automotive Radar Characterization: OTA HIL Testing for Enhanced ADAS Safety2026-26-00431/16/2026
The precise validation of radar sensor is necessary due to surging demand for reliable Advanced Driver-Assistance Systems (ADAS) and autonomous driving technologies. Over-the-Air (OTA) Hardware-in-the-Loop approach is the optimal solution for the current challenges facing with traditional on road testing. This approach supports productive, controllable and repetitive environment because of its lab-based setup which will eliminates the drawbacks such as high costs, limited repeatability, safety related issues. Key parameters of radar such as accurate detection of objects, analysis of doppler velocity, range estimation, angle of arrival measurement, can be tested dynamically. And this test setup offers wide range of testing scenarios, including varying distance of target, relative speeds, simulation of objects and environmental effects also supported.OTA provides the flexibility to eliminate the physical test tracks or targets so that developers can simulate the errors, by introducing faults into the systems and validate the compliances as per the industry standards, OTA HIL testing completely reduces development time and costs through enhancing test coverages, which will increase radar performance. This paper describes the system architecture, test plans, experimental results, demonstrate the critical role of OTA HIL in advancing automotive radar workflows and ensuring reliable ADAS and autonomous driving functionalities.
Jadhav, Tejas, Karle, Ujjwala, Paul, Harshit, SNV, Karthik
Mode Identification and Collaborative Switch for the Front-Centralized and Rear-Distributed Electric Drive Vehicle Based on BP Neural Network2025-01-733512/31/2025
Distributed-drive electric vehicles (DDEVs) significantly enhance off-road maneuverability but suffer from compromised high-speed stability and robustness. This research introduces a front-centralized and rear-distributed (FCRD) architecture that synergistically leverages the advantages of each configuration. The electric-drive-wheel (EDW) on the rear suspension can provide three working modes: (a) Drive-connected mode, (b) Drive-disconnected mode, (c) Brake mode. It is the key actuator for vehicle mode-switching, which supports the vehicle with three driving modes: (a) DDEV, (b) front-wheel drive (FWD), (c) all-wheel drive (AWD). A hierarchical control architecture employs the upper-layer controller with Back Propagation Neural Network (BPNN) for mode identification and decision-making. The lower-layer controller enables the intelligent torque distribution and collaborative control of the motors. The control strategy is pre-trained in the VCU (vehicle control unit) with off-line data annotations to achieve the maximal instantaneous system efficiency. At the same time, a cost function is designed to suppress unreasonable frequent mode switching that may deteriorate handling characteristics and ride comfort. The off-line data training results indicate that the overall accuracy of mode identification reaches 91.7%, of which the DDEV mode accuracy 98% and AWD mode accuracy 85%. Finally, the test vehicle with the calibrated EDW prototype is fully constructed and drives in Shanghai suburbs for a road test with parameters recorded throughout the whole cycle. The test vehicle has a balanced performance in power output, driving efficiency, and control robustness. The high-way cruising conditions activate the efficiency-oriented AWD mode of 82% overall propulsion system efficiency, which overcomes the problem of high-speed attenuation in electric vehicles and effectively improves the range at premise of safety and stability.
Ding, Xiaoyu, Chen, Xinbo, Wang, Wei, Zhang, Jiantao, Kong, Aijing
Road Test Emulation: A Data-Driven Calibration Approach2025-01-052111/25/2025
The resource-intensive process of road testing constitutes an essential part of the development of powertrain software. A significant proportion of explorative tests and adjustments for use in service are conducted during the vehicle test phase. However, the observed trends of decreasing development cycles and increasing system complexity generate a field of conflicts. In order to address this issue, this paper proposes road test emulation as a data-driven approach for continuously adapting powertrain software to the evolving overall system. A dedicated data strategy is designed to enhance customer-oriented software development. Therefore, test scenarios equivalent to in-service conditions are determined based on customer data. These test scenarios enable an emulation of road testing and the analysis of the system in a real-world operational context from the early stages of the product development process. System-specific data from the vehicle under development itself is utilised to define the initial parameter settings of the software. A generic approach to system-specific and customer-oriented calibration is presented. The example used is that of the causal, rule-based energy management of a performance-hybrid vehicle. This process results in the definition of an efficiency- and comfort-driven parameter set for the electric drive control, which is compared to a reference in various test scenarios. The method presented enables the data-driven generation of customer-oriented parameter sets and the quantification of the effects of comfort adjustments on the efficiency of the system in real-world operational contexts. Utilising software-in-the-loop simulations enables continuous implementation and iterative adjustments of the parameter sets and powertrain software throughout the product development process. The early consideration of in-service operations facilitates a shift-left in development activities. This supports an enhancement in the level of maturity at the beginning of road testing for the purposes of final calibration and testing of extreme conditions in the vehicle.
Martini, Tim, Kempf, André, Winke, Florian, Auerbach, Michael, Kulzer, André Casal
Development of an Artificial Calibrator for Shift Program Optimization to Enhance Fuel Efficiency2025-32-008211/3/2025
The calibration of automotive electronic control units is a critical and resource-intensive task in modern powertrain development. Optimizing parameters such as transmission shift schedules for minimum fuel consumption traditionally requires extensive prototype testing by expert calibrators. This process is costly, time-consuming, and subject to variability in environmental conditions and human judgment. In this paper, an artificial calibrator is introduced – a software agent that autonomously tunes transmission shift maps using reinforcement learning (RL) in a Software-in-the-Loop (SiL) simulation environment. The RL-based calibrator explores shift schedule parameters and learns from fuel consumption feedback, thereby achieving objective and reproducible optimizations within the controlled SiL environment. Applied to a 7-speed dual-clutch transmission (DCT) model of a Mild Hybrid Electric Vehicle (MHEV), the approach yielded significant fuel efficiency improvements. In a case study on a 4.7 km Worldwide harmonized Light-Duty vehicles Test Cycle (WLTC) driving segment, the RL-optimized shift strategy reduced fuel consumption from a baseline of 0.46 L to 0.37 L. Furthermore, when starting from an already optimized shift map representative of a series production vehicle’s calibration, the artificial calibrator further enhanced fuel efficiency, achieving approximately a 0.6 % reduction in fuel consumption for the 4.7 km segment and nearly a 5 % reduction for the full WLTC. The artificial calibrator thus demonstrates a promising methodology to frontload calibration tasks in simulation, thereby offering the potential to reduce reliance on resource-intensive physical testing and to significantly accelerate the development of fuel-efficient powertrain control software.. The direct compatibility of parameter files with real vehicle Electronic Control Unit (ECUs) and the validated SiL behavior suggest high transferability of learned strategies, offering the potential for minimal fine-tuning on physical vehicles post-simulation.
Kengne Dzegou, Thierry Junior, Schober, Florian, Rebesberger, Ron, Henze, Roman
Comparative Evaluation of Energy Efficiency and Performance of Electric and Counterpart Diesel Tractors2025-01-041710/7/2025
The objective of this trial was to compare the energy efficiency and performance of battery electric and conventional diesel tractors. Controlled road tests replicating normal operations were conducted using two electric and two diesel day-cab tractors. The test protocol was based on the TMC - Type III RP 1103A and SAE J1526 test procedures. The tests were conducted on a 110 km long route that included a 59 km hilly portion with a maximum altitude difference of 307 m. The tractors were divided into test groups of two vehicles. Trailers and drivers were switched throughout the trial between the tractors in a test group. The tests found that the two electric trucks consumed 60% and 63% less energy than their counterpart diesel trucks, respectively. Considering the average emission factor for production of electricity in Canada, the electric trucks emitted on average 82% less GHG emissions than the conventional diesel-powered tractors. The two diesel trucks showed similar fuel consumption and GHG emissions. The difference in electric energy consumption and GHG emissions between the two electric trucks was 7%. Energy and fuel consumption by route section was determined based on data from the vehicle electronic control modules. The trucks that showed the highest energy efficiency on the complete test route, also demonstrated the highest efficiency on specific sections of the test route. The regenerative braking system of the electric trucks charged the batteries with a regeneration ratio up to 38% on the descending section. Observations from drivers and observers were collected during testing. Generally, drivers would not hesitate to use the electric trucks especially if operability and battery range were improved. The driving experience with electric trucks was rated better than with diesel trucks.
Surcel, Marius-Dorin, Partington, Mark, Tanguay-Laflèche, Maxime, Schumacher, Richard
Revolutionizing Government Efficiency: Harnessing Commercial Off-the-Shelf Generative Artificial Intelligence Solutions for Enhanced Services and Decision-Making2025-01-04879/16/2025
This paper introduces a secure and cost-effective framework for integrating Commercial Off-the-Shelf (COTS) Generative Artificial Intelligence (GenAI) technology into government enterprise solutions. It explores key aspects of GenAI, emphasizing its transformative role in enhancing efficiency and decision-making within government operations. Central to the discussion is a GenAI Feasibility Study [1] conducted by Booz Allen for the Director, Operational Test & Evaluation (DOT&E), which outlines the development of the AI-Enabled Test & Evaluation Module (ATEM) GenAI Knowledge Assistant. The paper also examines critical factors for successful implementation, including use case definition, model selection, data quality, and prompt engineering.
Vandrovec, Bryan, Kruger, John, Birr, Calvin, Mazzara, Mark, Mossy, Glenn, Himmel, Max, Barnhart, James, Senger, Jeff
A Novel Mechanical Model Simulating a Pavement Deflection Measuring System for Non-Invasive Pavement Monitoring Based on a Reliability-Based Optimization Algorithm02-18-03-00259/4/2025
This article presents a novel mechanical model for simulating the behavior of pavement deflection measuring systems (PDMS). The accuracy of the model was validated by comparing the acceleration of the new model with the data achieved through experimental tests fusing a deflection measurement system mounted on a Ford F-150 truck. The experimental test for the PDMS is carried out on a random road profile, generated by an inertial profiler, over a 7.4-mile (12 km) loop around a lake near Austin, Texas. Integrating a reliability-based optimization (RBO) algorithm in a PDMS aims to optimize system parameters and reduce vibrations effectively. The PDMS noises and uncertainties make it crucial to use a robust system to ensure the stability of the system. This article presents a robust algorithm for considering the uncertainties of PDMS parameters, including the damping coefficients and spring stiffness of the supporting brackets. Moreover, it considers the variation of system parameters, such as stiffness of the vehicle’s tire and changing in the weight of the vehicle based on the number of passengers sitting in the cars. This approach ensures the system’s high accuracy and reliability, despite uncertainties and variations. Moreover, the presented algorithm calculates the optimum parameters of the PDMS model by minimizing the acceleration of the front and rear lasers and the rotation of the beam about the y-axis at the center of the beam. The accuracy of the RBO is being evaluated by comparing RBO with deterministic optimization methods. This comparison illustrates the accuracy of the RBO method for obtaining a more precise and reliable PDMS system. It also indicates the effectiveness of the RBO method in obtaining a more accurate and robust system, which can be utilized in real-world applications. RBO significantly minimizes the mean angular displacement of the beam (from 8.68° to 2.18°), as well as the RMS of front and rear accelerations (from 5.0 m/s2 to as low as 0.66 m/s2), based on variance reductions.
Yarmohammadisatri, Sadegh, Sandu, Corina, Claudel, Christian
Exploring the Correlation between Physiological States and Driving Behavior on Highways with Integrated ECG Measurements2025-01-02927/2/2025
Human driver errors, such as distracted driving, inattention, and aggressive driving, are the leading causes of road accidents. Understanding the underlying factors that contribute to these behaviors is critical for improving road safety. Previous studies have shown that physiological states, like raised heart rates due to stress and anxiety, can influence driving behavior, leading to erratic driving and an increased risk of accidents. In this study, we conducted on-road tests using a measurement system based on the Driver-Driven vehicle-Driving environment (3D) method. We collected physiological signals, specially electrocardiography (ECG) data, from human drivers to examine the relationship between physiological states and driving behaviors. The aim was to determine whether ECG can serve as an indicator of potential risky driving behaviors, such as sudden acceleration and frequent steering adjustments. This information enables automated driving (AD) systems to intervene in dangerous situations. We collected measurements from 22 participants, each tested for 15 minutes on the highway, resulting in a dataset of 330 minutes of physiological data and over 500 km of driving data. The data was segmented into 15-second intervals for detailed analysis. Each segment was labeled twice: physiological states classified as ’stress’ or ’relaxation’ based on heart rate derived from ECG, and driving styles categorized as ’defensive’, ’average’, or ’sporty’ based on CAN-Bus data. Preliminary findings revealed a significant correlation between overall driving behavior on the highway and physiological states. We selected key driving parameters, including velocity, acceleration, lateral acceleration, and yaw rate. We found that acceleration in longitudinal and lateral direction can best indicate driver control and intention, and they vary significantly under two physiological states. This study focuses on how physiological signals change during aggressive driving and aims to establish these signals as indicators for alerting drivers, ultimately reducing the risks of accident associated with aggressive driving behaviors.
Ji, Dejie, Flormann, Maximilian, Bollmann, Julian, Henze, Roman, Deserno, Thomas M.
Q&A25TOFHP06_146/1/2025
Last summer, SAE Media was invited to Eaton's proving grounds in Marshall, Michigan, to test drive an electric truck the company had built in collaboration with BAE Systems. The truck was a showcase not only of BAE's powertrain control technology, but also of Eaton's new multi-speed heavy-duty EV transmission. That truck was on display at the 2025 ACT Expo, as was Eaton's transmission. SAE Media spoke with Scott Adams, SVP of technology and global products for Eaton, in Anaheim, California, about the company's portfolio of multi- and single-speed medium- and heavy-duty transmissions as well as other upcoming driveline offerings.
Wolfe, Matt
Methods to Reduce Transmission of Airborne Viruses in a Bus Cabin02-18-04-00215/19/2025
Public buses can be high-risk environments for the transmission of airborne viruses due to the confined space and high passenger density. However, advanced cabin air control systems and other measures can mitigate this risk. This research was conducted to explore various strategies aimed at reducing airborne particle transmission in bus cabins by using retrofit accessories and a redesigned parallel ventilation system. Public transit buses were used for stationary and on-road testing. Air exchange rates (ACH) were calculated using CO2 gas decay rates measured by low-cost sensors throughout each cabin. An aerosol generator (AG) was placed at various locations inside the bus and particle concentrations were measured for various experiments and ventilation configurations. The use of two standalone HEPA air filters lowered overall concentrations of particles inside the bus cabin by a factor of three. The effect of using plastic “barriers” independently showed faster particle arrival times of 2–3 min and reduced particles concentrations by 20% compared to the baseline maximum concentration. The parallel system is 80% more effective in the removal of particles inside the bus cabin when compared to the conventional system. Installation of barriers makes the parallel system 70% more effective than the conventional system with barriers. Finally, filter efficiencies for new Minimum Efficiency Reporting Value (MERV) 13 filters were found to be higher than the pre-existing filters in the bus cabins due to electrostatic charge effect.
Lopez, Brenda, Swanson, Jacob, Dover, Kevin, Renck, Evan, Chang, M.-C. Oliver, Jung, Heejung
HV-Battery Impact on Car Body Acoustics and Damping Package Case Study of the Electric Vehicle2025-01-00415/5/2025
Damping treatments play a key role in the definition of efficient acoustic packages for passenger cars with all types of propulsion systems. Many damper configurations are similar for all vehicles including treatments of wheelhouses, spare wheel area, roof panels etc. However, there are some characteristics of car body acoustics in electric vehicles, which need to be considered in the definition of the efficient damping package. This paper investigates the impact of the high voltage (HV) battery on interior noise related characteristics of the car body using laser scanning vibrometry (LSV) and 3D sound intensity test methods. It is shown that both methods lead to similar conclusions in terms of proper distribution of damping material. Furthermore, findings are used in the damping package case study resulting in two additional proposals of the damping layout with different lightweight and acoustic requirements. Lab evaluation of the new damping package variants are conducted by laser vibrometry tests and the impact on interior noise is confirmed by road tests in the prototype vehicle.
Unruh, Oliver, Gielok, Martin
Leveraging User Feedback to Optimize the Tuning of EVSE Models2025-01-00205/5/2025
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.
Hank, Stefan, Kamp, Fabian, Gomes Lobato, Thiago Henrique
Research on In-Vehicle Clustered Multi-Channel Active Noise Control System2025-01-00165/5/2025
To address the issue of intermittent engine intervention during the charging and discharging processes of hybrid vehicles, which results in roaring noise within the cabin, this paper proposes a semi-coupled cluster control strategy that offers superior overall performance. This strategy is based on the traditional multi-channel Active Noise Control (ANC) system and integrates the advantages of both centralized and decentralized control approaches. The proposed clustered control strategy reduces computational load by approximately 50% compared to the centralized control strategy, while maintaining comparable noise attenuation performance. Moreover, it demonstrates significantly improved stability over the decentralized control strategy, with outstanding noise reduction results. Using the MATLAB simulation platform, the performance of the proposed in-vehicle clustered control strategy is compared with that of traditional control strategies. Additionally, road test experiments are conducted on a programmable electric vehicle under typical operating conditions to verify the strategy's effectiveness. The results indicate that the clustered control strategy is highly applicable to multi-channel ANC systems in vehicles, achieving average noise reductions of 6 dB(A), 19.7 dB(A), and 3.8 dB(A) for the 2nd, 4th, and 6th-order incremental programmer noise at the headrest positions of the four seats, respectively. These results demonstrate both effective noise reduction and stability. The findings hold significant scientific and engineering value and can be applied to noise control in manned environments, such as airplanes and submarines.
Deng, Huiping, Lu, Chihua, Chen, Wan, Liu, Zhien, Chen, Pian, Dou, Sirui, Sun, Menglei
Active Control of Engine Order Noise for Heavy-Duty Trucks: Using the Genetic Algorithm for the Optimization of Error Microphone Arrangement2025-01-00135/5/2025
The arrangement of error microphones for a vehicle active noise control (ANC) system is no trivial work, especially for heavy-duty trucks, due to the dilemma resulted from the large volume of the cab and the limited number of microphones accepted by most manufacturers in the auto industry. Although some pioneering work has laid the foundation for the application of numerical methods exemplified by the genetic-algorithm (GA) to optimize the error sensor arrangement in an ANC system, most ANC developers still resort to trial and error in practice, which is not only a heavy workload given the amount of interested working conditions to be tested, but also does not guarantee to yield the optimum noise cancellation performance. In this paper, the authors designed and implemented an error microphone selection process using a genetic-algorithm (GA) -based mechanism. The target vehicle was a heavy-duty truck with a six-piston diesel engine, and two application scenarios were particularly interested, i.e. driver & copilot and driver & one passenger sleeping on the berth. We first arranged nine microphones at different locations in the cab, five on the headrests, two on the B pillars and one at the head position of the sleeping berth. These locations were selected based on our empirical experience, the geometrical feature of the cab and the target application scenarios. With this layout, the engine-induced acoustic signals at the microphone positions along with the engine rotation rate under different working conditions (idling and constant speeds at different gears) were measured for subsequent analysis. Then, a GA-based numerical optimization targeting at reducing the major low-order engine noise using three error microphones was conducted, yielding that one error microphone on the B pillar, one on the headrest and one at the end of the sleeping berth led to the optimum noise attenuation performance. Road tests validated the numerical result.
Wang, Jian, Ling, Zihong, Zhang, Zhe, Cai, DeHua, lv, Xiao, Zhang, Ming, Gao, GuoRan
Drive Quality Evaluation for Chassis Dynamometer and On-Road TestingJ2951_202504 (Current)4/14/2025
This SAE Recommended Practice establishes uniform procedures for evaluating conformity between the actual and target drive speeds for chassis dynamometer and on-road testing utilizing standard fuel economy/energy consumption and emissions drive schedules.
Light Duty Vehicle Performance and Economy Measure Committee
Examination of the Data Structures of the Bendix® Data Recorder2025-01-87124/1/2025
Bendix® EC-80™ and certain EC-60™ ABS control units contain an event data recorder called the Bendix® Data Recorder (BDR). Raw BDR data is obtained using commercially available software, however, the translation of the raw data into an event report has only been performed by the manufacturer. In this paper, the raw data structures of the commercially available datasets are examined. It is demonstrated that the data follows uniform and repeatable patterns. The raw BDR data is converted into a conventional report and then validated against translation reports performed by the manufacturer. The techniques outlined in this research allow investigators to access and analyze BDR records independently of the manufacturer and in a way previously not possible.
DiSogra, Matthew, Hirsch, Jeffrey, Yeakley, Adam
A Novel Method for Evaluating on-Road Drag Changes Using Constant Power Measurements2025-01-87644/1/2025
This paper introduces a new approach for measuring changes in drag force across different vehicle configurations using an on-road testing technique. The method involves fixing the vehicle’s power across configurations and then measuring the resulting speed differences. A detailed formulation is provided on how these speed variations can be used to calculate the change in drag force for each configuration. The OBD II port is used to access and record additional data necessary for the calculations. The method is applied to both a passenger car and a commercial van to evaluate drag changes for different vehicle add-ons. A roof sign was installed at various positions along the roof of the vehicles to assess drag increases, while novel rear appendages were fitted to both vehicles to evaluate the resulting drag reductions. Detailed CFD simulations were performed on the road-tested configurations to compare the simulated drag changes with those measured on the road. Excellent agreement was found with the CFD results for both vehicles, with particularly strong correlation observed for the passenger car’s configurations. Finally, the paper describes how the method can be adapted to measure the baseline drag coefficient of a given vehicle. This involves attaching an elevated body to the vehicle’s towbar, which adds a known drag force to the setup. By measuring the speed change for the configured vehicle on the road, the baseline drag coefficient can be estimated.
Connolly, Michael Gerard, Ivankovic, Alojz, O'Rourke, Malachy J.
Adaptive Sliding Mode Control for Active Hydro-Pneumatic Suspension Based on Extended State Observer2025-01-82724/1/2025
Hydro-pneumatic suspension is widely used due to its favorable nonlinear stiffness and damping characteristics. However, with the presence of parameter uncertainties and high nonlinearities in the hydro-pneumatic suspension system, the effectiveness of the controller is often suboptimal in practical applications. To mitigate the influence of these issues on the control performance, an adaptive sliding mode control method with an expanded state observer (ESO) is proposed. Firstly, a nonlinear mathematical model of hydro-pneumatic suspension, considering seal friction, is established based on the hydraulic principle and the knowledge of fluid mechanics. Secondly, the ESO is designed to estimate the total disturbance caused by the nonlinearities and uncertainties, and it is incorporated into the sliding mode control law, allowing the control law to adapt to the operating state of the suspension system in real time, which solves the effect of uncertainties and nonlinearities on the system. Finally, the real road surface data are collected using laser displacement sensors and other devices to simulate the control effect of the proposed control method under real road surface conditions. The effectiveness of the adaptive sliding mode control method based on the ESO is verified through simulation. The results show that the RMS value of body acceleration is reduced by more than 50% and that it is robust to load variations when using the proposed method for the real road test, compared to the passive hydro-pneumatic suspension, which significantly improves the overall performance of the vehicle. This study provides some references for the design of active hydro-pneumatic suspension control methods.
Niu, Changsheng, Liu, Xiaoang, Jia, Xing, Gong, Bo, Xu, Bo
A Novel Hybrid Approach for Segmenting Drivers Based on Their Driving Style2025-01-82054/1/2025
Drivers present diverse landscapes with their distinct personalities, preferences, and driving habits influenced by many factors. Though drivers' behavior is highly variable, they can exhibit clear patterns that make sorting them into one category or another possible. Discrete segmentation provides an effective way to categorize and address the differences in driving style. The segmentation approach offers many benefits, including simplification, measurement, proven methodology, customization, and safety. Numerous studies have investigated driving style classification using real-world vehicle data. These studies employed various methods to identify and categorize distinct driving patterns, including naturalist differences in driving and field operational tests. This paper presents a novel hybrid approach for segmenting driver behavior based on their driving patterns. We leverage vehicle acceleration data to create granular driver segments by combining event and trip-based methodologies - subsequently, a clustering analysis groups drivers based on their performance during key driving events. The effectiveness of our proposed method is validated through a rigorous evaluation using a virtual driving simulator and three predefined driver types. The proposed approach showed promising accuracy and provided a reasonable and effective way to categorize the drivers. This method simplifies the complexity of driver behaviors, enables precise measurement, and leverages proven methodologies from other industries, ultimately contributing to safer and more personalized driving experiences. Driving style classification is a powerful means of invigorating and enriching research in many aspects of driving, especially within Autonomous Vehicles (AVs). This approach can potentially improve traffic safety and increase driver enjoyment and efficiency as fuel consumption.
Chavan, Shakti Pradeep, Chinnam, Ratna Babu
On-Road Investigation of Energy Saving Opportunity for Autonomous Light-Duty Vehicles through Automated Vehicle-Following in Safe Distance Scenarios2025-01-80294/1/2025
Reducing aerodynamic drag through Vehicle-Following is one of the energy reduction methods for connected and automated vehicles with advanced perception systems. This paper presents the results of an investigation aimed at assessing energy reduction in light-duty vehicles through on-road tests of reducing the aerodynamic drag by Vehicle-Following. This study provides insights into the effects of lateral positioning in addition to intervehicle distance and vehicle speed, and the profile of the lead vehicle. A series of tests were conducted to analyze the impact of these factors, conducted under realistic driving conditions. The research encompasses various light-duty vehicle models and configurations, with advanced instrumentation and data collection techniques employed to quantify energy-saving potential. The study featured two sets of L4 capable light duty vehicles, including the Stellantis Pacifica PHEV minivan and Stellantis RAM Truck, examined in various lead and following vehicle configurations at different speeds with cruise control enabled. Energy savings per km in the range of 9-17% were observed in Pacifica and savings up to 25% were obtained in RAM within 1-2 seconds following gap for speeds of 55-75 mph. It was also observed that the lateral positioning has a significant impact on energy saving overall. The results are also compared to the previous studies on drag reduction in two-vehicle platoons. This investigation contributes valuable knowledge to the vehicle-following to reduce the aerodynamic drag and thus to reduce the overall energy consumption in the highway driving scenarios. This can also be used in advanced vehicle positioning controls in autonomous vehicles where advanced sensing of the relative positions can be estimated accurately. The results give insights into optimizing energy efficiency, with a focus on the role of Vehicle-Following, aerodynamic drag reduction, and lateral positioning strategies for sustainable and environmentally conscious road transportation.
Poovalappil, Aman, Robare, Andrew, Schexnaydre, Logan, Santhosh, Pruthwiraj, Bahramgiri, Mojtaba, Bos, Jeremy P., Chen, Bo, Naber, Jeffrey, Robinette, Darrell
Sensor Cluster for Recording the Spread of Emissions in the Wake of a Vehicle2025-01-84924/1/2025
Progressive emission reductions and stricter legislation require a closer look at the emission behaviour of a vehicle, in particular non-exhaust emissions and resuspension. In addition to the analysis of emissions in isolation, it is also necessary to consider the impact of transport routes and dispersion potential. These factors provide insight into the movement of dust particles and, consequently, the identification of particularly vulnerable areas. Measurements using low-cost environmental sensors can increase the level of detail of dispersion analyses and allow a statement on the distribution of emissions in the vehicle's wake, as several measuring points can be covered simultaneously. A newly developed measurement setup allows vehicle emissions to be recorded in a plane behind the vehicle in a measurement area of 2 by 2 metres. The measuring grid consisting of 16 sensors (4x4 grid) can be variably positioned up to 1 metre from the rear of the vehicle. The sensors detect fine dust particles size-selectively (0.3 to 10 μm) in particle number and particle mass concentration, as well as VOC and NOx. The sensors also record air temperature and humidity to be able to establish correlations with the ambient conditions. It is shown that the particle dispersion in the flow wake of the vehicle changes with different driving scenarios. Furthermore, it is shown that the driving speed influences the turbulence potential due to resuspension and thus also the particle dispersion. The results obtained provide information on the particle movements behind a vehicle and thus on critical areas in the vicinity of roads. In this context, the resuspension of particles already deposited on the road surface is also becoming increasingly important.
Kunze, Miles, Ivanov, Valentin, Gramstat, Sebastian
Analysis of the Characteristics of Hybrid Vehicles and Low-Viscosity Lubricating Oil Based on Real Road Tests in Four Extreme Environments04-18-02-00091/7/2025
As countries around the world attach more importance to carbon emissions and more stringent requirements are put forward for vehicle emissions, hybrid vehicles, which can significantly reduce emissions compared with traditional fuel vehicles, as well as low-viscosity lubricating oil, have become significant trends in the industry. In this article, a total of nine vehicles of 48 V mild-hybrid models and full-hybrid models are tested. Using three kinds of low-viscosity lubricating oil and driving a total of 120,000 km in environments with low temperature, high humidity, high temperature, or high altitude, the engines are then disassembled and scored. The effects of the four extreme environments on the engine starts–stops, ignition advance angle, engine power, state of charge (SOC), acceleration performance, and oil consumption characteristics of hybrid vehicles are studied; the oxidation characteristics and iron content change characteristics of low-viscosity lubricating oil are analyzed; and how lubricating oil protects the engine in durability tests are verified. According to the test results, in the low-temperature environment, for full-hybrid models, the number of engine starts–stops and the running time are significantly increased, while the SOC is generally high. In the high-temperature environment, for full-hybrid models, the ignition advance angle of the engine is reduced, which inhibits the risk of pre-ignition; the characteristics of the SOC are similar to those in the high-humidity and standard-temperature WLTC working conditions; the oxidation rate of lubricating oil has almost no effect on full-hybrid models; for mild-hybrid models, oil is prone to oxidation and decay. In the high-humidity environment, the oil consumption rate deteriorates with the increase in relative humidity under the same load and engine speed, and the accumulation rate of iron content in oil increases compared with that in the high-temperature and high-altitude environments. In the high-altitude environment, with the increase in altitude, the engine power of full-hybrid models decreases at the same engine speed, resulting in a decrease in the engine’s charging efficiency to the battery, so that the battery level could not be relatively stable. The acceleration performance of both hybrid models decreases significantly with an increase in altitude. After the engines are disassembled, it is found out that with the protection of low-viscosity lubricating oil, the wear of engine parts is very small, and the deposit control is good.
Zhu, Gezhengting, Hu, Hua, Pan, Jinchong, Luo, Yitao, Hua, Lun, Jiao, Yan, Jiang, Jiandi, Shao, Heng, Xu, Zhengxin, Yan, Jingfeng, Wei, Guangyuan, Zhang, Heng
Mass Production Development of 4D Millimeter-Wave Radar Based on a Single Chip2024-01-702611/15/2024
In this paper, a single-chip based design for an automotive 4D millimeter -wave radar is proposed. Compared to conventional 3D millimeter-wave radar, this innovative scheme features a MIMO antenna array and advanced waveform design, significantly enhancing the radar's elevation measurement capabilities. The maximum measurement error is approximately ±0.3° for azimuth within ±50° and about ±0.4° for elevation within ±15°. Extensive road testing had demonstrated that the designed radar can routinely measure targets such as vehicles, pedestrians, and bicycles, while also accurately detecting additional objects like overpasses and guide signs. The cost of this radar is comparable to that of traditional automotive 3D millimeter-wave radar, and it has been successfully integrated into a forward radar system for a specific vehicle model.
Cai, Yongjun, Zhang, Xiansheng, Bai, Jie, Shen, Hui-Liang, Rao, Bing
Development and Experimental Validation of a Physics-Based Identification and Mitigation Strategy for Torsional Vibratory Behavior in Medium-Duty Commercial Vehicle Drivelines02-18-01-000111/8/2024
Torsional vibration generated during operation of commercial vehicles can negatively affect the life of driveline components, including the transmission, driveshafts, and rear axle. Undesirable vibrations typically stem from off-specification parts, or excitation at one or more system resonant frequencies. The solution for the former involves getting the system components within specification. As for the latter, the solution involves avoiding excitation at resonance, or modifying the parameters to move the system’s resonant frequencies outside the range of operation through component changes that modify one, or more, component inertia, stiffness, or damping characteristics. One goal of the effort described in this article is to propose, and experimentally demonstrate, a physics-based gear-shifting algorithm that prevents excitation of the system’s resonant frequency if it lies in the vehicle’s range of operation. To guide that effort, analysis was conducted with a numerical simulation model incorporating nonlinear driveline dynamics resulting from engine operation (including misfire and cylinder deactivation), excitation from multiple universal joints, the transmission, and a vehicle speed feedback controller, a contribution the authors have not seen in the pre-existing literature. The experimentally validated simulation results demonstrate that the torsional oscillating mode corresponding to the torque converter or turbine exhibits sensitivity to clutch activation, and variations in system parameters. Consequently, variation in system parameters alters the natural frequency of the system, potentially aligning it with the vehicle’s operational frequency range in specific gear ranges. Experimental on-road tests, described here, demonstrate that for the truck-under-test one of the natural frequencies of the system is within the range of operation for gears 4, 5, and 6 for certain vehicle speeds. Resonance in these gears was successfully prevented, and experimentally demonstrated, by using the proposed algorithm without sacrificing the performance of the vehicle.
Dhamankar, Shveta, Ali, Junaid, Parshall, Evan, Shaver, Gregory, Evans, John, Bajaj, Anil K.
Real-Time Implementable Reduced-Order Energy Model for an Electric Vehicle14-14-01-00068/22/2024
Accurate estimation of vehicle energy consumption plays an important role in developing advanced energy-saving connected automated vehicle technologies such as Eco Approach and Departure, PHEV mode blending, and Eco-route planning. The present study developed a reduced-order energy model with second-order response surfaces and torque estimation to estimate the energy consumption while just relying on the drive cycle information. The model is developed for fully electric Chevrolet Bolt using chassis dynamometer data. The dyno test data encompasses the various EPA test cycles, real-world, and aggressive maneuvers to capture most powertrain operating conditions. The developed model predicts energy consumption using vehicle speed and road-grade inputs for a drive cycle. The accuracy of the model is validated by comparing the prediction results against track and road test data. The developed model was able to accurately predict the energy consumption for track drive cycles within the error of ±4.0% of that measured from the experimental data. Finally, the model has been tested and verified for real-time implementation using the dSPACE MicroAutoBox II HIL test bench.
Goyal, Vasu, Dudekula, Ahammad Basha, Stutenberg, Kevin, Robinette, Darrell, Ovist, Grant, Naber, Jeffery
Driver–Steering Wheel Interaction during Cornering10-08-03-00247/24/2024
This research aims at understanding how the driver interacts with the steering wheel, in order to detect driving strategies. Such driving strategies will allow in the future to derive accurate holistic driver models for enhancing both safety and comfort of vehicles. The use of an original instrumented steering wheel (ISW) allows to measure at each hand, three forces, three moments, and the grip force. Experiments have been performed with 10 nonprofessional drivers in a high-end dynamic driving simulator. Three aspects of driving strategy were analyzed, namely the amplitudes of the forces and moments applied to the steering wheel, the correlations among the different signals of forces and moments, and the order of activation of the forces and moments. The results obtained on a road test have been compared with the ones coming from a driving simulator, with satisfactory results. Two different strategies for actuating the steering wheel have been identified. In the first strategy, the torque is provided mostly by just one single arm and hand. In the second strategy, the torque is created by both of the two arms and hands, which apply forces and moments in opposite directions. Future holistic driver models able to describe the forces acting at whole body may benefit from the outcomes of this research.
Previati, Giorgio, Mastinu, Gianpiero, Gobbi, Massimiliano
FMCW Lidar Simulation with Ray Tracing and Standardized Interfaces2024-01-29777/2/2024
In pursuit of safety validation of automated driving functions, efforts are being made to accompany real world test drives by test drives in virtual environments. To be able to transfer highly automated driving functions into a simulation, models of the vehicle’s perception sensors such as lidar, radar and camera are required. In addition to the classic pulsed time-of-flight (ToF) lidars, the growing availability of commercial frequency modulated continuous wave (FMCW) lidars sparks interest in the field of environment perception. This is due to advanced capabilities such as directly measuring the target’s relative radial velocity based on the Doppler effect. In this work, an FMCW lidar sensor simulation model is introduced, which is divided into the components of signal propagation and signal processing. The signal propagation is modeled by a ray tracing approach simulating the interaction of light waves with the environment. For this purpose, an ASAM Open Simulation Interface (OSI) object list referencing virtual 3D objects provides the input for the ray tracer. The divergence of the continuous laser beam is approximated by super-sampling the beam with multiple rays, the calculation of the received power is supported by the future ASAM OpenMATERIAL standard. Subsequently, the output of the ray tracer serves as the input of the signal processing that adapts the so-called Fourier tracing from the field of radar sensor simulation. This approach uses the range and velocity information of the individual rays to estimate the frequency spectrum of the intermediate frequency signal. A subsequent peak detection algorithm determines the output of the model, which is provided in the form of OSI lidar detections. Verification scenarios are tested to check the plausibility of the output and the source code of the signal processing is made available as open source.
Hofrichter, Kristof, Linnhoff, Clemens, Elster, Lukas, Peters, Steven
On-Center Steering Model for Realistic Steering Feel based on Real Measurement Data2024-01-29947/2/2024
Driving simulators allow the testing of driving functions, vehicle models and acceptance assessment at an early stage. For a real driving experience, it's necessary that all immersions are depicted as realistically as possible. When driving manually, the perceived haptic steering wheel torque plays a key role in conveying a realistic steering feel. To ensure this, complex multi-body systems are used with numerous of parameters that are difficult to identify. Therefore, this study shows a method how to generate a realistic steering feel with a nonlinear open-loop model which only contains significant parameters, particularly the friction of the steering gear. This is suitable for the steering feel in the most driving on-center area. Measurements from test benches and real test drives with an Electric Power Steering (EPS) were used for the Identification and Validation of the model. The open-loop architecture on steering rack level shows adequate results and generate a nearly delay-free response of the expected steering torque. Further it allows the expansion to a closed-loop or a hybrid model with neural networks. This makes it particularly suitable for force feedback systems in driving simulators or Steer-By-Wire Systems.
Dieing, Andreas, Reuss, Hans-Christian, Schlüter, Marco
Anti-Rollover Control for All-Terrain Vehicle Based on Zero-Moment Point2024-01-50554/30/2024
To investigate the rollover phenomena experienced by all-terrain vehicles (ATVs) during their motion caused by input from the road surface, a combined simulation using CarSim and Simulink has been employed to validate an active anti-rollover control strategy based on differential braking for ATVs, followed by vehicle testing. In the research process, a nonlinear three-degrees-of-freedom vehicle model has been developed. By utilizing a zero-moment point index as a rollover warning indicator, this approach could accurately detect the rollover status of the vehicle, particularly in scenarios involving low road adhesion on unpaved surfaces, which are characteristic of ATV operation. The differential braking, generating a roll moment by adjusting the amount of lateral force each braked tire can generate, was proved as an effective method to enhance rolling stability. Simulation and on-road testing results indicated that this control strategy effectively monitored the state of the ATV and enhanced the stability during rollover tests.
Hong, Hanchi, Wang, Kuan, d’Apolito, Luigi, Quan, Kangning, Yao, Xu
Effect of Shock Absorber Friction on Vehicle Vertical Dynamics10-08-02-00104/10/2024
In order to efficiently predict and investigate a vehicle’s vertical dynamics, it is necessary to consider the suspension component properties holistically. Although the effects of suspension stiffness and damping characteristics on vertical dynamics are widely understood, the impact of suspension friction in various driving scenarios has rarely been studied in both simulation and road tests for several decades. The present study addresses this issue by performing driving tests using a special device that allows a modification of the shock absorber or damper friction, and thus the suspension friction to be modified independently of other suspension parameters. Initially, its correct functioning is verified on a shock absorber test rig. A calibration and application routine is established in order to assign definite additional friction forces at high reproducibility levels. The device is equipped in a medium-class passenger vehicle, which is driven on various irregular road sections as well as over single obstacles. For all tested road sections, a linear decrease of ride comfort in terms of specific relevant vertical objective values is found by increasing the friction force. This emphasizes a definite link between suspension friction and vertical vehicle body vibration, resulting in a negative impact on vertical ride comfort. However, the longitudinal vehicle body vibration is not significantly affected. The relevance of friction in terms of transmitting the energy associated with road unevenness to the chassis in the frequency range of the chassis’ natural frequency is found to be remarkably high on smooth roads, and still considerably high on bumpy roads. The chassis and wheel resonance frequencies are significantly friction-dependent due to the damper’s slip or stick states. The results obtained from smooth road tests demonstrate the practical relevance of accurately considering friction for the given suspension type in terms of vertical ride comfort prediction.
Deubel, Clemens, Schneider, Scott Jarod, Prokop, Günther
Analysis of Low-Frequency Brake Noise for Drum Brakes on Semi-Trailers2024-01-28954/9/2024
A road test on semi-trailers is carried out, and accelerations of some characteristic points on the braking system,axles,and truck body is measured,also brake pressure and noise around the support frame is acquired.The measured data was analyzed to determine the causes of the brake noise, and the mechanism of the noise of the drum brake of semi-trailers during low-speed braking was investigated. The following conclusions are obtained: (1) Brake noise of the drum brake of the semi-trailer at low-frequency is generated from vibrations of the brake shoes, axle, and body, and the vibration frequency is close to 2nd natural frequency of the axle. (2) Brake noise is generated from stick-slip motion between the brake shoes and the brake drum, where the relative motion between the brake drum and the brake shoes is changed alternately with sliding and sticking, resulting in sudden changes in acceleration and shock vibration. A multi-body dynamic model of the semi-trailer is established for analyzing vibrations causing noise and the influencing parameters. In the model, the elastic deformation of components, such as brake drums, brake shoes, axles, and leaf springs during the braking process, is considered. The model is validated by comparing calculated data with experiment data.The simulation shows that there is a heavy stick-slip vibration between the brake drum and brake shoes, which is transmitted to the axle through the brake shoes, and then to the body through the leaf spring. As the speed of the semi-trailer increases, the stick-slip frequency between the frictional pairs increases. When the stick-slip frequency is close to the natural frequency of the axle, it resonance.
Tang, Hao, Shangguan, Wen-Bin, Kang, Yingzi, Zheng, Jing-Yuan, Lan, Wen-Biao
Numerical Simulation of Fluctuating Wind Noise of a Vehicle in Reproduced on-Road Wind Condition2024-01-23534/9/2024
In vehicle development, reducing noise is a major concern to ensure passenger comfort. As electric vehicles become more common and engine and vibration noises improve, the aerodynamic noise generated around the vehicle becomes relatively more noticeable. In particular, the fluctuating wind noise, which is affected by turbulence in the atmosphere, gusts of wind, and wake caused by the vehicle in front, can make passengers feel uncomfortable. However, the cause of the fluctuating wind noise has not been fully understood, and a solution has not yet been found. The reason for this is that fluctuating wind noise cannot be quantitatively evaluated using common noise evaluation methods such as FFT and STFT. In addition, previous studies have relied on road tests, which do not provide reproducible conditions due to changing atmospheric conditions. To address this issue, automobile manufacturers are developing devices to generate turbulence in wind tunnels. However, in wind tunnels, it is difficult to reproduce the large length-scale fluctuations of natural winds, and it could not sufficiently simulate the road conditions. In this study, we simulated the fluctuating wind that vehicles experience on the road and verified the fluctuating aerodynamic noise. We first reproduced wind noise under steady flow conditions and confirmed that the pressure fluctuation measured on the side window matched well with wind tunnel results up to 2 kHz. Furthermore, it was confirmed that using modulation power spectrum analysis, it is possible to quantitatively evaluate the fluctuating wind noise compared with FFT and STFT. From these results, we found that fluctuating wind noise is an acoustic phenomenon in which the aerodynamic noise generated around the vehicle is amplitude-modulated by fluctuations in the mainstream velocity. The technical challenge is to understand the separation flow around the A-pillar and side mirror, which generates fluctuating wind noise.
Tajima, Atsushi, Ikeda, Jun, Nakasato, Kosuke, Kamiwaki, Takahiro, Wakamatsu, Junichi, Oshima, Munehiko, Li, ChungGang, Tsubokura, Makoto
Braking Judder Test and Simulation Analysis of Commercial Vehicle2024-01-23424/9/2024
Brake judder affects vehicle safety and comfort, making it a key area of research in brake NVH. Transfer path analysis is effective for analyzing and reducing brake judder. However, current studies mainly focus on passenger cars, with limited investigation into commercial vehicles. The complex chassis structures of commercial vehicles involve multiple transfer paths, resulting in extensive data and testing challenges. This hinders the analysis and suppression of brake judder using transfer path analysis. In this study, we propose a simulation-based method to investigate brake judder transfer paths in commercial vehicles. Firstly, road tests were conducted to investigate the brake judder of commercial vehicles. Time-domain analysis, order characteristics analysis, and transfer function analysis between components were performed. Subsequently, a multi-body dynamics model of the commercial vehicle was established using ADAMS software, and the effectiveness of the model in predicting brake judder characteristics and transfer functions was verified through experiments. Under braking conditions, transient simulation analysis was carried out to obtain the acceleration of key components along each transfer path. The contribution of each component was then determined using a transfer path analysis method. Research shows that judder causes larger vibrations near the excitation end, showing clear order relationships at 2-4, 6, and 9 orders. However, components like the steering wheel, brake pedal, and cab seat have smaller vibrations with no clear order relationships. Modifying the structure of the steel plate spring can reduce braking judder. The simulation model accurately predicts the time-domain and frequency-domain characteristics of braking judder.
Huang, Dehui, Zhang, Kai, Sun, Jichao, Li, Wenbo, Pei, Kaikun
Analysis and Improvement of the Cabin Low Frequency Noise Caused by Underbody Rear Cavity Airflow Oscillation in the Pure Electric Vehicle High Speed Cruise2024-01-23504/9/2024
During the pure electric vehicle high speed cruise driving condition, the unsteady air flow in the chassis cavity is susceptible to self-sustaining oscillations phenomenon. And the aerodynamic oscillation excitation could be coupled with the cabin interior acoustic mode through the body pressure relief vent, the low frequency booming noise may occur and seriously reduces the driving comfort. This paper systematically introduces the characteristics identification and the troubleshooting process of the low frequency aerodynamic noise case. Firstly, combined with the characteristics of the subjective jury evaluation and objective measurement, the acoustic wind tunnel test restores the cabin booming phenomenon. The specific test procedure is proposed to separate the noise excitation source. Secondly, according to the road test results, it is inferenced that the formation mechanism of low frequency noise is the self- sustaining oscillation with the underbody shedding vortex feedback enhancement mechanism at the bottom of the rear chassis. The low frequency exterior airflow oscillation is coupled with the interior cabin acoustic modality by the two air relief vents located at the vehicle rear body parts. Furtherly, the modal coupling mechanism is verified by the volumetric acoustic source excitation test in the semi-anechoic chamber. Considering the engineering feasibility and cost, some improvement schemes are proposed and verified by comparison. Finally, the cover of the vehicle body pressure relief vent is determined to the actual application, the cabin noise level in the specific low frequency band is reduced by 10 dB(A). This paper provides a guiding reference for solving the similar low frequency noise problem of electric vehicles at the high-speed cruise condition.
Shen, Long, Zhang, Jun, Gu, Perry
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