Road Test Research Articles

Dynamic Testing of In-Wheel Motor Based Electric Vehicle in Longitudinal Direction

This paper presents an investigation into the performance of in-wheel motor (IWM) based electric vehicles (IWM-EV) in the longitudinal direction. The design of IWM-EV is an innovation of the conventional go-kart vehicle with slightly modifications in steering, suspension, and braking system, which then makes use three-phase permanent magnet synchronous in-wheel motor (PMSM-IWM) at both of the rear axle wheels. An extension of that is a simulation of IWM-EV vehicle using a 5-degree-of-freedom vehicle longitudinal model that has been developed by incorporating PMSM-IWM as a drive wheel located at the rear axles. Using the simulation, vehicle dynamic control in the longitudinal direction-based Proportional-Integral-Derivative (PID) controller has also been strategized. As the intention to confirm the capability of the IWM-EV, experimental studies-based real IWM-EV hardware have been conducted. Three dynamic tests that generalized from SAE standard SAE J866-199908, namely acceleration performance at the level pavement (include acceleration tests and acceleration then braking tests) and road gradient tests at constant speeds of 10, 15 and 20 km/h, were used as the testing method. The performance areas evaluated were vehicle body speed, wheel speed, distance travel experienced by the vehicle, IWMs current, drive torque as well as the battery voltage capacity used by the vehicle. The finding indicate that the simulation results and experimental data are similar with less than 5 % error. The outcomes from this study will be considered in the design optimization of a torque vectoring control in the next research study.

Cloud-Based Optimization of a Battery Model Parameter Identification Algorithm for Battery State-of-Health Estimation in Electric Vehicles

Connectivity and cloud computing are key elements in the future of electric mobility. They allow manufacturers to provide advanced fleet management and predictive diagnostic services. In particular, cloud computing dramatically enhances data availability and enables the use of more complex and accurate state estimation algorithms for electric vehicle lithium-ion batteries. A tuning procedure for a moving window least squares algorithm to estimate the parameters of a 2-RC equivalent circuit battery model is presented in this paper. The tuning procedure uses real data collected from a test vehicle and uploaded to the Stellantis-CRF cloud. The tuned algorithm was applied to eight months of road tests and showed very small estimation errors. The errors are comparable to other literature data, even when the literature results were obtained in laboratory tests. The estimated model parameters are tracked through time and seem accurate enough to show the first signs of battery aging.

Estimation of Road Roughness Based on Both the Sprung and Unsprung Response of a Moving Vehicle Over Ordinary Roads: Modeling, Experiments and Discussions

The study proposes a Kalman Filter Family-schemed algorithm to identify the vehicle’s parameters and evaluate the road roughness simultaneously, based on the response of an adapted monitoring vehicle. The vehicle is simplified as a three-dimensional multi-body system consisting of the unsprung mass of wheels and the sprung mass of the car body, connected by springs and dampers that represent the suspension system. Accelerometers and a gyroscope measure the accelerations or angular velocity of different positions of the vehicle during vibrations. The Kalman filter (KF) with unknown inputs enables the prediction of the car body’s accelerations from those of wheels. On the other hand, the Augmented KF can compute the accelerations of wheels based on the car body’s accelerations. Thus, an inner-systemic objective function incorporating the vehicle’s parameter is built between the predicted and measured accelerations and solved in an optimized manner with the Genetic Algorithm, so that an individual complicated impact test or bump test is avoided. The numerical examples carry out field tests on a 900[Formula: see text]m long standardized test road under two scenarios of with and without a bump. The road roughness estimated by these two KF methods from different measurements is used to calculate the International Roughness Index (IRI) and further the Riding Quality Index, which are compared with those directly provided by a standardized laser IRI profilometer. Accordance in between confirms the accuracy of the proposed algorithm under different scenarios. The analysis underlines the measurements from unsprung wheels that contact directly with the road enable a more accurate estimation of road roughness than those from the sprung car body. In addition, a vehicle speed lower than 40[Formula: see text]km/h can provide a better estimation of the road profiles.

Using case study on the performance of rural cement stabilizing construction waste recycling road base

In order to solve the problem of resource utilization of construction waste (C&W) recycled aggregate (RA) in rural road grassroots, natural aggregate (NA) was replaced by RA with 0%, 20%, 40%, 60%, 80% and 100% in the test. The unconfined compressive strength, splitting strength, compressive resilience modulus, dry shrinkage test, and frost resistance test were used to test the road performance of the recycled mixture. In order to improve the strength and crack resistance of cement stabilized regenerated mixture, three different admixtures (polypropylene fiber, expansion agent, and curing agent) were considered based on the orthogonal test to improve the crack resistance of the regenerated mixture, and their influence weights were analyzed. Relying on the Gaobeidian rural road network reconstruction project, the construction waste recycling test road was laid, and the construction quality of compaction, bending, and flatness was tested. The results show that the strength of cement-stabilized recycled mixture peaks when RA content is 20%. When RA content is 0% to 100%, the compressive strength decreases by 22.6%, compressive resilience modulus decreases by 18.7%, and tensile strength decreases by 33.2%. Adding 0.8‰ polypropylene fiber, 0.4% expansion agent, and 1.5% curing agent increased 21.2% 7d unconfined compressive strength, 7.8% in 7d splitting strength, and 43.2% in 14d drying shrinkage coefficient. The construction test results show that adding fiber and low-content construction waste increases the base load capacity, increases the compressive strength by 34.5%, reduces the base deflection by 10.5%, and has good road performance. Finally, considering the test results comprehensively, when the RA content is below 20%, and the polypropylene fiber content is between 0.6‰ and 0.8‰, it can meet the basic construction requirements of secondary and sub-secondary rural regeneration roads in China.

A novel regenerative braking energy recuperation system for electric vehicles based on driving style

The regenerative braking energy recovery system of pure electric vehicle is to recover and reuse the consumed driving energy under the premise of ensuring the braking safety. In this paper, the regenerative braking energy recovery system of pure electric vehicle was optimized based on driving style, and the driver model is constructed and the parameters that characterise driving style are determined. BLSTM (Bidirectional Long Short Term Memory) neural network model method was introduced for deep self-learning, and IDP (Iterative dynamic programming)-BLSTM based regenerative braking energy recovery management control strategy was established. Through theoretical analysis and numerical model of the system, the results of parameter representation of the energy system were preliminarily evaluated and road test was carried out. The results of real vehicle test show that IDP-BLSTM method can meet the personalized requirements of various drivers, improve driving experience and safety, and recover braking energy efficiently.

Construction Technology and Pavement Performance of Dry-Mix Polyurethane Modified Asphalt Mixtures: A Case Study

Polyurethane Modified Asphalt Mixture (PUAM) has been confirmed to possess good engineering properties and is a potential replacement material for pavement construction. This study aimed to provide guidance for the promotion and application of PUAM in pavement engineering by exploring the construction technology and verifying the practicality. Dry-mix PUAM (DPAM), wet-mix PUAM (WPAM), and SBS-modified asphalt mixture (SBSAM) were prepared. After systematically investigating the construction process of the three mixtures, their pavement performance was comparatively evaluated. Subsequently, the DPAM was utilized to construct the trial pavement, and the completed pavement was tested and evaluated. Furthermore, the costs of the DPAM and SBSAM were analyzed. The results reveal that the construction technology had a significant effect on the mechanical properties of the mixtures. Compared with SBSAM, the optimum mixing temperature and time of the DPAM and WPAM were reduced. The mixing temperature, mixing time, and hitting number were recommended to be 160 °C, 60 s, and 75 times for the DPAM. Fourier Transform Infrared Spectroscopy tests confirmed that the PU reacted sufficiently in the binder. The DPAM exhibited good overall pavement performance, and its low-temperature cracking and fatigue resistance were significantly better than that of SBSAM. Meanwhile, all the pavement indexes constructed with DPAM met specifications, and the performance and service condition of the test road after the operation will be paid attention to continuously. Additionally, the cost of DPAM was close to that of SBSAM, and the more straightforward construction process and better pavement performance of DPAM could reduce the construction energy consumption and maintenance frequency, which was meaningful for promoting the scale application of DPAM and the sustainable development of transportation infrastructure.

Towards nationwide implementation of 40% biodiesel blend fuel in Indonesia: a comprehensive road test and laboratory evaluation

This research focused on evaluating the technical viability of using biodiesel with a blending ratio of 40% v/v, which is expected to be implemented soon in Indonesia. Two kinds of biodiesel blends were prepared, a blend of 60% diesel fuel and 40% biodiesel (B40) and a blend of 60% diesel fuel, 30% biodiesel, and 10% hydrogenated vegetable oil (HVO) (B30D10). The fuels were tested on EuroII vehicles without any engine modifications through a 50,000 km endurance road test. Laboratory tests were also performed at certain traveled distances to evaluate various engine parameters, including power, fuel economy, exhaust emissions, and used engine oil properties. Engine components were inspected upon the completion of the road test. Cold-start ability was also examined to confirm the suitability of the investigated biofuels at low-temperature operating conditions in Indonesia. The road test results showed that vehicles fuelled with B40 and B30D10 could reach a distance of 50,000 km without encountering any technical issues. The laboratory evaluation during the road test indicated that B30D10 had a higher power and fuel economy than B40, with a maximum difference of 2%. Furthermore, B30D10 emitted lower CO, HC, and PM emissions than B40 throughout the distance traveled, with maximum differences of 11.4%, 14.7%, and 22.6%, respectively, but led to 15% higher NOx. Engine component inspection and used engine oil analysis confirmed the fulfillment of the manufacturer's recommendations for both B40 and B30D10. Finally, B40 and B30D10 were suitable for operating at low ambient temperatures in Indonesia, confirming them as practical options to be implemented in the nationwide 40% biodiesel blend fuel.

Reducing the Fuel Consumption of an Hybrid Electric Vehicle With the Use of Model Predictive Control-Case Study

The article presents operational aspects related <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">to energy management strategy (EMS) - model predictive control (MPC). The mathematical model showing the synergy of working machines of the hybrid electric vehicle (HEV) was presented. Then the results of road tests have been shown. They were based on the factory control of the above-mentioned system. The results of the operating parameters of the system according to the factory control and the results of the operating parameters according to the MPC with different linear quadratic tracking (LQT) curves were compared. Application of thirteen reference LQT trajectories results in lower fuel consumption of the HEV. It led to changes in the power and the battery state of charge (SOC): for factory control - from 50.1% (the beginning) to 56.1% (the end of course) and for MPC from 50.1% (the beginning) to 59.9% (the end of the course). The applied MPC with 13 reference trajectories (LQT) of power machines of the series-parallel HEV allowed for fuel savings on the level of 4%.

Traffic Flow Pattern Based Approach to Predict Real Driving Emission Test Routes

Due to the poor representation of NEDC emission test, the European Commission put into the force a new procedure, which contains both a laboratory test and a real word driving test. In this new test procedure, even though WLTC replaces NEDC, it is required to test the vehicle under real traffic conditions, which contains urban, rural and highway segments. Due to the new emission regulation, considerable number of academic work focus on the creation of RDE (Real Driving Emission) routes and RDE tests. In this study, it is introduced a new methodology for creating potential RDE routes. The routes, created in MATLAB code by using Istanbul road data containing a half an hour average trip records were used to predict a probable RDE test road. This model creates a number of RDE routes starting from defined coordinates and then analyses all alternative routes with respect to traffic flow rate and RDE boundary conditions identified by the European Commission. The routes obtained using the methodology developed are tested in real life conditions and evaluated according to actual existing traffic conditions. The agreement between the results of the method and the results of the actual driving test is limited in urban road section. However, for rural and highway road sections, there is a significant agreement between the predictions and actual test results.

Discussion on the Status Quo of Non-Destructive Testing Technology in Highway Engineering and Strategies of Improving the Quality of Testing

Highway test and detection technology play a very important role in controlling the quality of road and bridge engineering and improving the maintenance of roads and bridges. The study of highway bridge test detection technology is both theoretically and practically useful. Road and bridge test and detection is a complicated task. With the development of science and technology highway and bridge engineering test and detection technology has also made great progress. The continuous improvement of test and detection technology has brought good social benefits to road and bridge construction. This article discusses the problems in test and detection technology of highway bridges and how to improve the quality of test and detection.

Investigation of the performance of cement-stabilized magnesium slag as a road base material

The harmless, resource-saving, and large-scale utilization of magnesium slag (MS) from industrial waste has become an important topic for road research. The use of MS as a substitute for aggregate is a practical and efficient way to dispose of it. However, there is a lack of systematic research on how to standardize its use in road construction. The objective of this study was to investigate the applicability and feasibility of using MS for cement stabilized base course materials. The influence of different cement dosages, curing age, and gradation on the strength, stiffness and stability of cement-stabilized magnesium slag mixture (CMSM) was investigated, and the actual road performance of CMSM was analyzed by paving a test road. The results showed that the mechanical properties of the CMSM met the requirements for road base courses under medium-to-light traffic when the cement dosage was above 5%. The unconfined compressive strength loss rate of the CMSM was less than 13% for an immersion time of 1 to 7 days, and after 5 freeze–thaw cycles, the frost resistance coefficient of the CMSM was more than 85%. The performance of the CMSM was most affected by cement dosage and curing age, closely followed by mixture grading type. MS can enhance the development of the pozzolanic reaction, resulting in improved strength and compactness of CMSM. Overall, CMSM exhibited exceptional road performance and could reduce aggregate costs by 25% to 35%. The use of MS as an aggregate for road base courses offers a sustainable solution that not only maximizes the use of solid wastes, but also avoids the potential safety hazards and environmental pollution caused by improper disposal and stockpiling of MS.

Experimental investigation on exhaust emissions of a heavy-duty vehicle powered by a methanol-fuelled spark ignition engine under world Harmonized Transient Cycle and actual on-road driving conditions

Compared to the conventional fossil fuels, methanol is a renewable, environment-friendly, and inexpensive oxygenated fuel. In this work, to explore the feasibility of using methanol as a substitute for diesel or gasoline in internal combustion engines, the exhaust emissions of a heavy-duty vehicle powered by the methanol spark ignition (SI) engine are tested under the World Harmonized Transient Cycle (WHTC) and actual on-road driving conditions. The results indicate that the brake specific CO, NOx, PM, and non-methane hydrocarbon emissions of the heavy-duty engine fuelled with methanol under the WHTC are lower than those of the engine fuelled with diesel and diesel-gasoline. However, the NH3 emission of the heavy-duty engine fuelled with natural gas is much higher than that of the methanol-fuelled engine, and exceeds the China VI emission standard. Under the actual road test, CO emission decreases once the exhaust temperature of the test vehicle reaches up to 250 °C, while NOx emissions are maintained at a relatively low level and then sharply increase at the initial cold-start of the road test. However, NOx emissions increase with further increase in the exhaust temperature.

Testing and performance analysis of an integrated electromagnetic and hydraulic retarder for heavy-duty vehicles

Hydraulic retarder and eddy current retarder are important auxiliary braking component, which installed on heavy-duty vehicles. However, the hydraulic retarder has poor braking performance at low speeds, while the eddy-current retarder presents serious thermal recession at high speed. To overcome these issues and ensure safe driving during downhill conditions, a novel Integrated Electromagnetic and Hydraulic Retarder (IEHR) is proposed. The design includes a rotor with blades, double salient poles, and a coil built in a C-type stator. The electromagnetic field model of the IEHR is established and analyzed using the Finite Element Method. Moreover, the nonlinear eddy viscosity model of the flow field is generated and analyzed using the Computational Fluid Dynamics. The Blend braking control strategy is adopted to distribute the braking torque at high speed and low speed The IEHR performance was tested at a test bench. The test results show that the calculated braking characteristics of the electromagnetic and hydraulic subsystems were reasonable agreement with the measured results. The road test was carried out on a vehicle with a total mass of 49 tons. The deceleration and torque peaked at 0.75 m/s2 and 3620 N m, respectively. These results indicated that the IEHR has better performance than conventional hydraulic retarders and eddy current retarder, and is more suitable for heavy vehicles.

Use of waste rubber particles in cement-stabilized aggregate for the eco-friendly pavement base layer construction: Laboratory performance and field application

The waste tires were utilized for cement-stabilized aggregate (CSA), which could alleviate the environmental problems caused by waste tires and improve the durability of CSA. In this study, rubber particles with sizes ranging between 2.36 ∼ 4.75 mm were added to the CSA and replaced natural aggregate. The rubberized cement-stabilized aggregate (RCSA) was designed in the laboratory and verified in the field test road. The CSA and RCSA specimens were prepared by static pressure compaction and vertical vibration compaction in the laboratory and from field cores. The unconfined compressive strength test, indirect tensile strength test, fatigue test, dry shrinkage test, and temperature shrinkage test were adopted to evaluate the performance of RCSA. The results showed that the addition of rubber reduced the compressive and indirect tensile strength of CSA. However, the vibration compaction method could significantly alleviate the negative impact of rubber on strength reduction. The rubber particles could improve the deformation capacity and fatigue performance of CSA, and the maximum increase in ultimate failure strain was 21.5%. The dry shrinkage strain and dry shrinkage coefficient of CSA were reduced by 12.0% and 18.4%, respectively. The temperature shrinkage strain and temperature shrinkage coefficient decreased by 29.2% and 28.4% after adding rubber particles, respectively. Rubber could improve the durability and cracking resistance of CSA. The RCSA provided an option for an environmentally friendly pavement base layer.

Physical and chemical characteristics of particles emitted by a passenger vehicle at the tire-road contact

Non-exhaust emissions are now recognized as a significant source of atmospheric particulate matter and the trend towards a reduction of conventionally fueled internal combustion engine vehicles on the road is increasing their contribution to air pollution due to lower exhaust emissions. These particles include brake wear particles (BWP) and tire-road contact particles (TRCP), which are composed of tire wear particles (TWP), road wear particles (RWP) and resuspended road dust (RRD). The goal of this study has therefore been to design an original experimental approach to provide insight into the chemical composition of particles emitted at the tire-road contact, focusing on the micron (PM10–1μm) and submicron (PM1–0.1μm) fractions. Through this characterization, an examination of the different TRCP generated by different materials (tire, road surface, brake system) was conducted. To achieve this, TRCP were collected at the rear of the wheel of an instrumented vehicle during road and track tests, and a SEM-EDX analysis was performed. Our experimental conditions have allowed us to demonstrate that, at the individual particle scale, TRCP are consistently associated with road dust materials and particles solely composed of tire or road materials are practically non-existent. The contribution of BWP to TRCP is marked by the emission of Fe-rich particles, including heavy metals like Ba, Mn and Cr. TWP, which result from rubber abrasion, consist of C-rich particles abundant in Si, Zn, and S. RWP, mainly composed of Al, Si, Fe, and Ca, can be either part of RRD or internally mixed with emitted TWP. The findings of this study highlight the substantial role of RRD to TRCP emissions under real driving conditions. Consequently, it underscores the importance of examining them simultaneously to achieve a more accurate estimation of on-road traffic emissions beyond the vehicle exhaust.

Analysis of passenger car powertrain system measurements in road conditions

The paper is focused on presenting a methodology for measuring power and torque based on diagnostic equipment available in most diagnostic workshops, such as OBD interfaces or the CAN Bus on-board data transmission network, under real-world road conditions. The publication presents an algorithm for calculating the powertrain’s torque and power based on measurements of changes in vehicle speed or acceleration recording during a two-phase road test. The results presented, based on the method described, apply to both the internal combustion and electric vehicle. Common powertrain operating parameters, such as maximum power, maximum torque and the powertrain’s flexibility parameters described in the literature are proposed for the final evaluation of the vehicle’s traction system.

A Fuzzy-Based Slip Resistive Controller for Front Wheel Drive Autonomous Electric Vehicle

The direction and eternal theme of the automotive industry’s sustainable development is protection of the environment, energy efficiency, and safety. Especially the traffic accidents, the world’s energy shortages and the increasingly deteriorating environment are particularly important today. Especially in current era, because of the dual pressures of energy and the environment, various forms of electric vehicles (EVs) are becoming the focus of global automotive industry. This paper presents a significant method of road recognition method. The key control is to have the option to precisely recognize the ideal slip rate and current street surface attachment coefficient to control the wheel slip. By utilizing the Burckhardt strategy, the slant change of the bend could sort out the ideal slip rate and pinnacle attachment coefficient of street surface distinguishing proof examination is generally utilized in steadiness control of EV. On road tests, the road conditions are very complicated. It is necessary to take identify methods with strong robustness. Therefore, it is an important method to use fuzzy technique with good robustness to recognize optimal slip rate (OSR). The fuzzy road recognition algorithm could identify the friction co- efficient and the OSR superiorly.

Study on fatigue damage evolution and model prediction of asphalt pavement in the end-stage of service

Through the use of the material test system (MTS), bending fatigue tests are conducted in this work in order to investigate the attenuation law of fatigue performance of asphalt pavement in the end-stage of service. Response surface methodology (RSM) is used to analyze the effects of strain, frequency, and temperature on the asphalt surface layer's initial stiffness, fatigue life, phase angle, and cumulative dissipated energy when there is a 50 % reduction in the initial stiffness. Through multi-factor coupling analysis, the optimal combination is found and verified by the MTS-810 test system. Based on this, the data of the initial stiffness declining to 20 % was used for analysis on the AC-13C asphalt surface mixture of the APT full-size test road in the laboratory. At 15 °C and 10 Hz, the evolution law of the flexural stiffness, the residual stiffness, phase angle, and cumulative dissipated energy of the asphalt mixture was investigated. Analysis of the asphalt mixture's damage evolution under the single stage of loading and various strain levels revealed changes in the fatigue cracking crack. Beam specimens were made from asphalt mixture field test beams of AC-13C (laboratory accelerated pavement test road), AC-20C, and AC-25C (Ji-Qing expressway) to conduct four-point bending fatigue test (4PB). According to the constant strain fatigue prediction equation, and the residual fatigue life of prediction localized model was established. The results show that the influence of frequency and temperature on the initial stiffness and phase angle is more significant than strain, and the influence of strain on number of fatigue is more significant. The flexural stiffness of the asphalt mixture shows an obvious S-curve, and larger the tensile strain at the bottom of the asphalt layer, shorter the time needed to reach the termination condition, that is, the faster the fatigue failure occurs. When the damage termination condition is reached, under the strain level of 200–300 με, 60 % of the number of loading produce about 35–40 % damage, and the remaining 20 % of the number of loading lead to 10–20 % damage.

Regenerative Braking Control Strategy Based on Pavement Recognition Controller for Electric Vehicle

Regenerative braking is a key technology for electric vehicles to improve energy efficiency and extend driving range. Considering the impact of road surface adhesion coefficient in the regenerative braking process of vehicles is a meaningful but challenging problem. To effectively utilize the pavement adhesion coefficient and improve the brake energy recovery effect, a pavement observer‐based regenerative braking control strategy for pure electric vehicles is proposed. The control strategy can identify the pavement based on correction factor by analogy idea according to the real‐time state information of vehicles. The optimal braking force distribution coefficient under different pavements is obtained by Fmincon function based on interior point algorithm. The effectiveness of the control strategy is verified by Simulink/CarSim software cosimulation and road test. The results show that the braking time of the proposed regenerative braking control strategy is reduced by 8.2% and the average actual feedback braking torque is increased by 17.6% in dry asphalt conditions compared with the fixed proportional distribution control strategy. Under the premise of effectively ensuring the braking stability and safety of the vehicle, more energy generated during braking can be recovered.

Uncertainty Analysis and Design of Air Suspension Systems for City Buses Based on Neural Network Model and True Probability Density

The accuracy of uncertainty analysis in suspension systems is closely tied to the precision of the probability distribution of sprung mass. Consequently, traditional assumptions regarding the probability distribution fail to guarantee the accuracy of uncertainty analyses results. To achieve more precise uncertainty analysis outcomes, this paper proposes a data-driven approach for analyzing the uncertainties in bus air suspension systems. Firstly, a bus vehicle dynamics model is established to investigate the influence of sprung mass on suspension system performance. Subsequently, a deep neural network model is trained using road test data, for the accurate identification of the sprung mass. The historical mass of the bus is then computed using vehicle network data to obtain the true probability density of the sprung mass. Lastly, the real probability distribution of the sprung mass is utilized to perform uncertainty analysis on the bus suspension system, and the results are compared with those obtained by assuming a probability distribution. Comparative analysis reveals substantial disparities in uncertainty response, with a maximum relative error of 9% observed for wheel dynamic loads, thus emphasizing the significance of precise probability distribution information concerning the sprung mass.