Test Vehicle Research Articles

Research on Dual-Actuator Shift Control of Dual-Mode Coupling Drive Electric Vehicles

Dual-mode coupling drive system can improve the dynamic performance of electric vehicles through mode switching, and the quality of mode switching directly affects the comfort of drivers and passengers. Mechanical coupling on the left and right sides of the single actuator causes mutual interference during shifting, resulting in prolonged power interruption time and shifting shock. Therefore, this paper analyzes the mutual interference mechanism of single-actuator shifting, designs a new dual actuator, and proposes a staged fuzzy PID controller. Finally, the effectiveness of dual-actuator shifting is proven through simulations and real vehicle testing. Compared with conventional PID control and BP neural network PID control, the shock degree is reduced by 64% and 50%, which improves the mode-switching quality of the dual-mode coupling drive system.

Study on instrumental coupler for heavy haul train

As a crucial load-bearing component, coupler’s safety is pivotal for sustainable railway industry development and is extensively scrutinized due to its complex loading environment. However, current research predominantly concentrates on the longitudinal dynamic behavior of couplers, neglecting factors such as nodding and shaking during traversals along curves and ramps. This study proposes an innovative method aimed at identifying multiple loads on couplers, which includes longitudinal tension and compression, lateral shaking, and vertical nodding forces. A theoretical load identification method based on strain sum and difference on coupler shank faces under various loading scenarios is established by finite element analysis. To facilitate accurate measurement, Wheatstone bridges are employed for three-dimensional force measurement, facilitating strain calculation and temperature compensation. The validity of the proposed approach is confirmed through comprehensive validation, encompassing finite element simulation, laboratory experimentation, and vehicle tests. Results demonstrate the robustness of the method, with maximum load deviations of 2.32% longitudinally, 22.52% horizontally, and 19.86% vertically observed during laboratory tests. Results indicate the proposed method’s accuracy and efficiency in heavy haul train coupler load assessment.

Virtual Tools for Testing Autonomous Driving: A Survey and Benchmark of Simulators, Datasets, and Competitions

Traditional road testing of autonomous vehicles faces significant limitations, including long testing cycles, high costs, and substantial risks. Consequently, autonomous driving simulators and dataset-based testing methods have gained attention for their efficiency, low cost, and reduced risk. Simulators can efficiently test extreme scenarios and provide quick feedback, while datasets offer valuable real-world driving data for algorithm training and optimization. However, existing research often provides brief and limited overviews of simulators and datasets. Additionally, while the role of virtual autonomous driving competitions in advancing autonomous driving technology is recognized, comprehensive surveys on these competitions are scarce. This survey paper addresses these gaps by presenting an in-depth analysis of 22 mainstream autonomous driving simulators, focusing on their accessibility, physics engines, and rendering engines. It also compiles 35 open-source datasets, detailing key features in scenes and data-collecting sensors. Furthermore, the paper surveys 10 notable virtual competitions, highlighting essential information on the involved simulators, datasets, and tested scenarios involved. Additionally, this review analyzes the challenges in developing autonomous driving simulators, datasets, and virtual competitions. The aim is to provide researchers with a comprehensive perspective, aiding in the selection of suitable tools and resources to advance autonomous driving technology and its commercial implementation.

Research and application of rapid reconstruction technology to existing bridge guardrails based on UHPC connection

A novel prefabricated segmental guardrail is proposed to facilitate connections between guardrails and between guardrails and bridge decks by casting ultrahigh-performance concrete (UHPC) joints in situ. Through finite element crash simulation analysis of three types of vehicles and crash tests of real vehicles, the prefabricated segmental guardrail with a UHPC connection was systematically evaluated in terms of its energy-absorbing capacity, vehicular acceleration, post-impact trajectory of the impacting vehicle, and behaviour of the guardrail upon impact. During the evaluation process, performance comparisons of the prefabricated segmental guardrails are made with the monolithic concrete guardrails. The results indicate that the performance of the prefabricated segmental guardrail with a UHPC connection was superior to that of the conventional concrete monolithic guardrails: it exhibited a higher level of crash performance, the occupants of the impacting vehicle were better protected, and the impacting vehicle exhibited better post-collision stability. Finally, the convenience of the prefabricated segmental guardrails with UHPC connections was proven in practical engineering applications.

Influence of rotating wheels on Reynolds number sensitivity of passenger vehicle drag

Rotating wheels are essential to replicate realistic forces and flow fields during aerodynamic testing of passenger vehicles. Previous studies have found that the drag coefficient typically reduces with increased speed under rotating wheel conditions but is stable with stationary wheels. This paper investigates this velocity sensitivity for two vehicles, the aerodynamic research vehicle DrivAer and a production vehicle. Experiments with the DrivAer indicate that the drag reduction with increased speed cannot be explained by pressure changes on the vehicle body; instead, the effect is attributed to local flow changes around the wheels. Using numerical simulations, it is found that the separation at the front wheels' outer tire shoulder increases for lower velocities, thus resulting in higher drag coefficient and causing Reynolds number sensitivity. The degree of drag reduction is less for the DrivAer squareback than for the notchback due to the separation over the notchback's rear window. No direct difference is measured between various tires and rims. To assess the generality of the findings with the DrivAer, the results are compared to experiments with a production vehicle. It is observed that the drag sensitivity is less and only occurs if the rear wheels are rotating. Pressure measurements in the wheelhouses and around the wheel drive units confirm the front wheel separation's dependence on velocity and highlight the complex interaction between the front wheel wakes and rear wheel rotational state.

Analysis of Seat Vibration during High-Speed Driving for a Certain Vehicle Model

Abstract To address the seat shaking issue of a certain vehicle model under high-speed conditions, this article utilizes the TPA method, starting from the “source-path-response” perspective. By comparing with benchmark vehicles’ lateral parameters, it confirms the abnormal vibration frequency of the seat as 12Hz in the Z direction. Through real vehicle testing, the validity of this approach is verified, providing clear optimization solutions and improvement suggestions for subsequent vehicle NVH design.

Drive Cycle‐Based Estimation of Energy Consumption for Electric Two‐Wheeler

ABSTRACTThe transportation sector is the backbone of the economic growth of any country. However, the heavy dependence of this sector on petroleum fuel is a matter of concern for sustainable development. To address this issue countries are working toward green energy‐based transportation, and among all viable solutions electric vehicles (EVs) are emerging as front runners. Range anxiety is one of the most prominent concerns in EV adoption. The range of a vehicle depends on the energy consumption so it becomes crucial to estimate it very precisely. There are many standard drive cycles such as the New European Driving Cycle (NEDC) and Worldwide harmonized Light‐duty Vehicle Test Cycles (WLTC) which are used for the estimation of energy consumption. However, these standard cycles fail to capture the driving behavior of real traffic. Due to this reason, these standard cycles underestimate the energy consumption compared with actual consumption. For more realistic energy requirement estimations, researchers are focusing on the development of real‐world drive cycles specific to a particular geography. In this paper, a real‐world drive cycle of electric two‐wheeler has been developed for the city of Lucknow, India, and compared with the driving characteristics and energy consumption estimates of WLTC. The energy requirement per km for the Lucknow drive cycle and WLTC are found as 14.89 Wh/km and 11.95 Wh/km, respectively, which indicates per km energy required estimation for LDC is 24.60% higher than WLTC.

Dual‐inertia flywheel energy storage system for electric vehicles

AbstractManaging the high‐rate‐power transients of Electric Vehicles (EVs) in a drive cycle is of great importance from the battery health and drive range aspects. This can be achieved by high power‐density storage, such as a high‐speed Flywheel Energy Storage System (FESS). It is shown that a variable‐mass flywheel can effectively utilise the FESS useable capacity in most transients close to optimal. Novel variable capacities FESS is proposed by introducing Dual‐Inertia FESS (DIFESS) for EVs. The feasibility of the proposed concept is evaluated by deriving the size of a Single‐Inertia FESS (SIFESS) for a battery EV, which runs the well‐known Urban Dynamometer Driving Schedule. The sizing framework consists of an Energy Management System using the constrained Pontryagin's minimum principle and a proposed sizing algorithm. Then, by splitting the derived SIFESS inertia into two separate inertias, the appropriate engaging control of inertias is determined for some driving cycles including, the Artemis Urban, Braunschweig City, and Worldwide Harmonised Light‐duty Vehicles Test Cycle. The dual inertias suitable sizes are derived using a proposed algorithm, which targets maximising the FESS useable capacity. The results show that compared to the SIFESS, the DIFESS can employ the FESS's useable capacity more effectively.

Enhancement of rider comfort by magnetorheological elastomer based damping treatment at strategic locations of an electric two wheeler

The vibrations generated in the two-wheeled vehicles like motorcycles due to road irregularities such as cracks, potholes, and bumps on the road cause discomfort for the rider as well as the pillion. These vibrations are reported to cause lower back pains, musculoskeletal effects, fatigue, and long-term health issues. Particularly, electric two-wheelers are more susceptible to these vibrations caused by the road and need attention. This paper presents an innovative technique for the reduction of vibrations at prominent locations in the electric two-wheeler to improve the rider’s comfort. All measured accelerations are about vertical direction (along z-axis as per ISO 2631-1 standard). Passive and Semi-active damping treatments namely, Room temperature vulcanizing Silicone rubber and Magnetorheological elastomer (MRE) were applied on the test vehicle at strategic locations of vibration. Both were compared for their effectiveness in reducing the vibrations. Results showed that MRE based damping technique proved better vibration isolation at the strategic locations. The weighted root mean square acceleration as well as vibration dose values were found to decrease with the help of damping treatments thus improving the rider’s overall comfort level.

Regenerative Braking Conscious Rule-Based Energy Management Strategy for Semi-Active Hybrid Energy Storage Systems for Electric Vehicles

Hybrid Energy Storage Systems (HESS) function as a solution to extend the lifespan of battery packs by maintaining a low charge/discharge rate. The integration of HESS in electric vehicles (EVs) is facilitated by supercapacitors (SC), known for their safe operation even under harsh conditions. The widely adopted rule-based power follower energy management strategy (EMS) is employed to control and restrict battery discharge within a defined range with SC support. Additionally, it charges the SC to accommodate regenerative energy, but it often neglects exploring the SC voltage set reference. This study investigates the SC voltage reference point and introduces a method to generate the reference point by equating the SC energy with the available kinetic energy in the moving vehicle. The proposed method was simulated and compared against the benchmark method using a portion of the medium segment Worldwide Harmonized Light Vehicles Test Procedure (WLTP) driving cycle. The results demonstrate a more stable discharge power for the battery bank, accompanied by improvements in battery voltage stability. The root mean square (RMS) battery current values were found to be 43.68 A and 42.92 A for the benchmarked and proposed methods, respectively, indicating a slight improvement of about 1%. Furthermore, the proposed method reduces the voltage deviation from 2.73% to about 2.57%, showcasing an additional positive outcome. These findings suggest that dynamically adjusting the SC voltage based on kinetic energy can enhance battery life and stability in EVs, offering a promising direction for future research and development of EMS.

Investigating Blind Spot Design Effects on Drivers’ Cognitive Load with Lane Changing: A Comparative Experiment with Multiple Types of Intelligent Vehicles

Lane changing is a frequent traffic accident scenario. To improve the driving safety in lane changing scenarios, the blind spot display of lane changing is increased through human–machine interaction (HMI) interfaces in intelligent vehicles to improve the driver’s rate of risk perception with regard to the driving environment. However, blind spot information will increase the cognitive load of drivers and lead to driving distraction. To quantify the coupling relationship between blind spot display and drivers’ cognitive load, we proposed a method to quantify the cognitive load of the driver’s interaction by improving the AttenD algorithm, collecting feature data by carrying out a variety of real-vehicle road-testing experiments on three kinds of intelligent vehicles, and then establishing a model blind spot design and driver cognitive load correlation model using Bayesian Logistic Ordinal Regression (BLOR) and Categorical Boosting (CatBoost). The results show that the blind spot image display can reduce the driver’s cognitive load more effectively as it is closer to the driver, has a larger area, and occupies a higher proportion of the center control screen, especially when it is located in the middle and upper regions of the center control screen. The improved AttenD algorithm is able to quantify the cognitive load of the driver, which can be widely used in vehicle testing, HMI interface development and evaluation. In addition, the analytical framework constructed in this paper can help us to understand the complex impact of HMI in intelligent vehicles and provide optimization criteria for lane change blind spot design.

Enhancing perception of vehicle motion by objective positioning of the longitudinal axis of rotation in driving simulators

The automotive industry is heading towards a more objective approach to vehicle testing, but subjective evaluation is still an important part of the development process. Subjective evaluation in physical testing has environmental implications and is dependent on ambient conditions. A more repeatable, faster, safer and more cost-effective tool for subjective evaluation is to use moving base driving simulators. The motion cueing algorithms (MCA) maps the movement of the vehicle into the limited space of the simulator. The choice of reference point, that is, where on the vehicle to sample the motion to feed to the MCA and the alignment of the axis of rotation of the simulator cabin is still an open topic. This paper investigates the choice of reference point and corresponding simulator longitudinal axis of rotation in roll using two methods. The first method uses a linearised model of the combined system of vehicle, simulator and vestibular models. The second method, to position the cabin longitudinal axis of rotation, is based on offline optimisation. The linear model can capture important characteristics of the specific forces and rotations that are fed to the driver through the motion cueing algorithms and offers a method to objectively analyse and potentially tune the motion cueing. The analysis is further complemented with a subjective evaluation of corresponding settings. The results from the linear model, the offline optimisation and the subjective evaluation shows that a reference point at the driver’s head has a clear advantage over the full frequency range compared to a reference point in the chassis roll axis and that the positioning of the cabin longitudinal axis of rotation has a significant effect on the perceived vehicle characteristics.

Review of Vehicle Scanning Method for Bridges from 2004 to 2024

The vehicle scanning method (VSM), originally known as the indirect method, is an efficient method for bridge health monitoring that utilizes mainly the responses collected by the moving test vehicles. This method offers the advantage of mobility, efficiency, and cost-effectiveness as it requires only one or a few vibration sensors mounted on the test vehicle, eliminating the need for deployment of numerous sensors on the bridge. Since its initial proposal by Yang and co-workers in 2004, the VSM has gained intensive attention from researchers worldwide. Over the past two decades, significant progress has been made in various aspects of the VSM, including the identification of bridge frequencies, mode shapes, damping ratios, damages, and surface roughness, as well as its application to railways. Previously, some review papers and the book Vehicle Scanning Method for Bridges were published on the subject. However, research on the subject continues to boom at a speed that cannot be adequately by existing review papers or book, as judged by the fast-increasing number of relevant publications. In order to provide researchers with an overall understanding of the up-to-date researches on the VSM, a state-of-the-art review of the related research conducted worldwide is compiled in this paper. Comments and recommendations will be provided at appropriate points, and concluding remarks, including future research directions, will be presented at the end of the paper.

Impact of traffic signs on driving speed at mountain highway tunnel entrances − The role of low-volume intermittent information

Driver’s perception of speed is the basis of driving safety, and installing speed limit signs at tunnel entrances is an intuitive means of controlling a driver’s driving speed. Therefore, tunnel entrance signs should be set up effectively to ensure each signage can fulfil its intended effect. Quantifying the information volume conveyed by traffic signs, discovering the impact of different information volumes on driving speeds, and understanding the effects of typical signs are the prerequisites for the effective use of signage. This study collected the speed variations of 40 drivers driving at nine mountainous highway tunnels with different entrance traffic signs through a naturalistic driving real vehicle test. The effect of low-volume intermittent information at tunnel entrances is identified in terms of the black hole effect on drivers (BHD), white hole effect on drivers (WHD), velocity fluctuation trend (VFT), and effect of speed limit signs (ELS). The study’s results confirm that the effect of speed limit signage with traffic sign information volume (TSIV) in the range of 8.904 to 33.318 bit is significant. In comparison, the sign will lose its effectiveness in guiding drivers to control their speed when TSIV is greater than 58.641 bits. Using low-volume information speed limit signs or tunnel warning signs repeated twice before entering a tunnel can alert drivers and regulate their driving speeds. The speed limit sign (sign ①) for each type of vehicle is set individually, and the combined speed limit and no lane change sign (sign ②) used in two stacks have a strong speed control effect. Moreover, the sign ②, when used alone, has the best timeliness; the effective distance of speed control can reach 1522 m; using it before short tunnels or long tunnels less than 1500 m can achieve better effectiveness.

Field study on vibration characteristics of geocell-reinforced aeolian sand subgrades

Constructing highways in deserts is expensive due to the difficulty of acquiring materials; utilizing aeolian sand effectively has become a problem, especially in the Xinjiang region, where the desert widely occurs. This paper aims to investigate the vibration response of a geocell-reinforced aeolian sand subgrade under traffic loading based on field tests of highways in deserts. The vibration acceleration response of geocell-reinforced aeolian sand and gravelly soil upper roadbed structures is tested. The field test results illustrate the effects of dynamic loading on geocell-reinforced aeolian sand roadbeds, and the thickness substitution ratio between geocell-reinforced aeolian sand roadbeds and conventional gravelly soil roadbeds is determined and verified based on the vibration acceleration monitoring values. The results show that the vibration response induced by the test vehicle is concentrated within the 30 Hz frequency band, and the higher the vibration frequency, the faster the vertical decay in the road. The vibration damping capacity of the reinforced aeolian sand roadbed is better than that of the gravelly soil roadbed; when replacing the gravelly soil roadbed with the reinforced aeolian sand roadbed, the substitution ratio is 0.31–0.42. It is verified that half thickness of gravel soil on roadbeds can be replaced by geocell-reinforced aeolian sand under different working conditions. The results of this study can provide reference data for the design of highway subgrades in deserts.

Research on Optimal Driving Torque Control Strategy for Multi-Axle Distributed Electric Drive Heavy-Duty Vehicles

Multi-axle distributed electric drive heavy-duty vehicles have the characteristics of high transmission efficiency, strong maneuverability, and good passability, making them widely used in large cargo transportation. However, the current driving torque control strategies of multi-axle distributed electric drive heavy-duty vehicles lack comprehensive consideration of their longitudinal and lateral dynamic characteristics, making it difficult to comprehensively optimize multiple performances such as power economy, comfort, and stability. In order to solve the above problems, This work focuses on a five-axle distributed electric drive heavy-duty vehicle. Firstly, given the differences in dynamics between two-axle vehicles and multi-axle vehicles, the dynamic model of the multi-axle distributed electric drive heavy-duty vehicle and its critical components is constructed. Then, by analyzing the characteristics of power economy, comfort, and stability of the multi-axle distributed electric drive heavy-duty vehicle, an optimal driving torque control strategy based on multiple performance coordination is proposed. Finally, on the hardware-in-the-loop (HiL) platform, the performance of the optimal driving torque control strategy proposed in this paper is verified by using the China Heavy-Duty Commercial Vehicle Test Cycle for Truck (CHTC-HT) and a straight-line acceleration driving condition on a split friction road. The simulation test results show that, compared with the traditional torque average distribution strategy, the proposed optimal driving torque control strategy can reduce the energy consumption rate by 3.45% in CHTC-HT. The strategy is attributed to the driving torque distribution based on the vehicle’s optimal instantaneous energy consumption, and vehicle comfort is also ensured by the driving mode switching frequency suppression. Subsequently, the vehicle’s stability on the split friction road is effectively improved by the torque coordination compensation strategy. This control strategy significantly improves the comprehensive performance of multi-axle distributed electric drive heavy-duty vehicles.

Energy-saving drive control strategy for electric tractors based on terrain parameter identification

Emissions from agricultural production already have a significant impact on the global environment. New energy, zero-emission electric tractors have great potential for application. How to further reduce energy consumption under the premise of ensuring operational stability is an urgent problem to be solved to realize the broad application of electric tractors. For this purpose, this paper proposed an energy-saving drive control strategy for electric tractors based on terrain parameter identification. At first, the longitudinal dynamics model and load transfer model of the electric tractor were established by considering the terrain information of the area to be operated. Mathematical principles for adjusting wheel slip to reduce energy consumption in electric tractors are presented. Then, a wheel longitudinal force estimation algorithm was designed based on the principle of sliding-mode observer and dynamics compensation. To achieve energy-saving drives for electric tractors, a particle filter based on a wheel-soil model was designed to identify terrain parameters in real time and calculate the optimal slip to control the torque of the drive motor. Lastly, the strategy is validated by hardware-in-the-loop (HIL) simulation tests and real-vehicle tests. HIL tests show that this strategy results in a 25.35% increase in operational speed stability and a 6.79% reduction in operational energy consumption compared to the conventional drive control strategy. The real vehicle test shows a 45.09% increase in operating speed stability and a 9.51% reduction in total energy consumption of the proposed method. The proposed drive control strategy reduces operational energy consumption and operational costs on the premise of ensuring the stability of operational speed, which is conducive to the implementation of cleaner production.

SmartSiC™ Substrates: A Boon to Drain Metallization Process

We present results of epitaxial characterization and benchmarking of Silicon Carbide (SiC) epitaxial layers grown on both 6-inch commercially available SiC substrate and on SOITEC’s new generation SmartSiCTM substrate. Multi wafer reactor was utilized to avoid run-to-run variation. Schottky Barrier Diodes (SBD) and electrical test vehicles were fabricated to extract ideality factor, barrier height and ohmic contact resistance for benchmarking.

Temporary Road Marking Paint for Vehicle Perception Tests

In order to test camera- and LiDAR-based perception of road markings for automated driving, vehicle developers have started to utilize concepts for the agile alteration of road marking patterns on proving grounds. Road marking materials commonly used within this concept are different types of tape that can easily be applied and removed on asphalt and concrete. Due to the elasticity of tape, it cannot be used efficiently for small radii, symbols, lettering, and specific corner shapes (e.g., for parking slots). These road marking patterns are common in urban environments. With the growing capability of automated driving systems and more applications for urban environments, edgy road marking shapes gain importance for proving ground testing. This study examines the use of water-soluble road marking paint specifically designed for the use case of temporary applications on proving grounds for camera- and LiDAR-based perception testing. We found that white, water-soluble paint with 1.5% binder content and 2.25% coalescing agent content can provide realistic road markings for vehicle testing purposes. However, solubility affects the paint’s vulnerability to fading during rain. Hence, renewal activities over the course of longer test drives might be necessary. The paint could be removed using water pressure without significant residue or damaging of the asphalt.

Development of Driving Robot and Driver Model Applied Regenerative Brake Control of Electrified Vehicles

Real driving emissions (RDE) test procedures for type approval were initiated in Japan in 2022. In Japan, the test vehicle is driven on a test road (test course) by tracing the speed pattern prepared for each RDE test. The vehicle needs to trace the patterns in the same manner as in the conventional chassis dynamometer test. The use of a driving robot is effective for reproducibility in precisely tracing the target vehicle speed during these tests. In this study, we developed a driving robot for electrified vehicles (HEV, plug-in HEV, BEV, and FCV), which have regenerative brake-control systems. We applied a new logic to our robot that was developed in-house for conventional engine vehicles. We focused on braking deceleration of the regenerative brake control to change the operation timing from the accelerator pedal to the brake pedal. We verified the improvement of speed traceability of the driving robot installed with the proposed logic on the chassis dynamometer and test road.