Test Vehicle Research Articles

Working cycle condition construction for electric wheel loader based on principal component analysis and cluster analysis

With the rapid development of new energy technology, cycle condition is significant for the design of powertrain system, whole machine economy, endurance, and other performance parameters of pure electric drive machines. Many cycle conditions of the passenger car industry have been defined. While that for the loader which has complex operation modes and working conditions, has less research on this aspect. Cycle conditions suitable for loader have not been constructed. To support the research and development of electric loader power system, the cycle conditions that can reflect the driving characteristics of electric loader are studied in this paper. According to the typical “V” cycle condition of loader, the actual driving condition data are collected and the kinematic segments are divided. The kinematic segments are grouped into five categories by using principal component analysis and K-means clustering algorithm to obtain the clustering center of each category. The working cycle condition is formed by extracting the combination of segments closest to the clustering center. Finally, based on AMESim simulation and whole machine test analysis, the error between the simulation and vehicle test results of the energy consumption is 3.4%. The accuracy and effectiveness of the proposed constructed cycle conditions are verified.

Cooling performance and optimization of a thermal management system based on CO2 heat pump for electric vehicles

Efficient integrated thermal management scheme is crucial for improving the driving range, thermal comfort, and safety of electric vehicles. Compared with the synthetic refrigerant heat pump indirect cooling/heating on the vehicle electrical system, the natural refrigerant CO2 heat pump direct thermal controlling integrated into the thermal management system has advantages in the thermal cycle performance and environmental friendliness. The present study proposed a thermal management system based on CO2 heat hump with multiple working modes for enhancing vehicle energy utilization coefficient. The system thermal performance under the World Light Vehicle Test Cycle was investigated via energy and exergy analyses. The operational control strategies of the thermal management system were optimized for the thermal controls of the cabin, battery and motor. The results show that the minimum exergy destruction of the thermal system occurs at the optimal discharge pressure corresponding to the highest coefficient of performance. Ensuring two-phase latent heat transfer for battery cooling is the most effective measure to maintain battery temperature uniformity via dynamic collaborative regulation of expansion valves’ openings and compressor speed. Compared with constant expansion valve’s opening, the coefficient of performance of the system can be improved by a maximum of 10% with the saturated CO2 vapor at the outlet of battery cooling plate. Due to the low thermal capacitance and minimal thermal inertia of driving motor, its cooling performance is significantly influenced by the heat generation rate and refrigerant flow. Optimal motor cooling efficiency is achieved when controlling the refrigerant quality to 0.85 at the cooling passage outlet. Under the World Light Vehicle Test Cycle, the thermal management system effectively regulated the temperatures across different operating modes while operating at optimal discharge pressures.

The New Cyberlinktech, Inc. Resilience to Creating Growth Model

The New Cyberlinktech, Inc. (TNCI) operates in a highly dynamic and evolving market, requiring the need for a strategic business plan to sustain growth and adaptability. The New Cyberlinktech, Inc. (TNCI) is one of the leading information technology providers for Private Emission Testing Centers (PETCs) under the Department of Transportation and the Land Transportation Office in the Philippines. TNCI faces significant challenges in the current market landscape, including increasing regulatory pressure against PETCs, the emergence of the Motor Vehicle Inspection System (MVIS) as an alternative mode of vehicle testing, and the frequent leadership changes and abrupt policy shifts at the Land Transportation Office (LTO) and the Department of Transportation (DOTr). To ensure sustainability and adaptability, this dissertation aims to develop a comprehensive business plan for The New Cyberlinktech, Inc. (TNCI) that addresses the challenges posed by the rapidly changing market landscape including a 5-year roadmap. The research design employs a mixed methods approach. The qualitative phase involves conducting interviews with key stakeholders within TNCI, including senior management, employees, and selected industry experts. Through these qualitative interactions, the study aims to identify the specific challenges faced by TNCI in the evolving market and explore potential strategic approaches to address them. In the quantitative phase, the focus is on using surveys among the current clients of the company to determine the preferred IT projects that they want the company to implement in the future. The quantitative analysis provides a comprehensive assessment of TNCI’s current performance, identifies potential risks and opportunities, and informs the development of strategic recommendations. The integrated analysis phase synthesizes the findings from the qualitative and quantitative data. By comparing and contrasting the insights gained from both approaches, a holistic understanding of the challenges and opportunities facing TNCI is achieved. The strategic business plan is formulated based on the integrated analysis, considering the specific needs and goals of TNCI. The plan encompasses strategies to address regulatory challenges, navigate the MVIS landscape, manage leadership changes, adapt to policy shifts, and recommend potential IT projects that the company can adapt and implement. Potential findings may include insights into the specific regulatory pressures faced by PETCs, the implications of the MVIS on TNCI’s business model, and strategies to mitigate the effects of leadership and policy changes. The implications of the research findings can inform TNCI’s decision-making process and help guide the company in sustaining growth and adaptability in the rapidly evolving market. This dissertation contributes to the body of knowledge by providing a comprehensive strategic business plan tailored to TNCI’s context. The findings and recommendations have practical implications for TNCI and other IT companies operating in similar environments. Future research opportunities may involve evaluating the implementation and effectiveness of the proposed business plan and exploring additional strategies to enhance TNCI’s competitive advantage in the PETC industry. Keywords: Strategic continuity, Business plan, Sustainability, Adaptability, Private Emission Testing Centers, Motor Vehicle Inspection System, Regulatory pressure, Leadership change, Policy shifts, mixed methods researc

Inclined Obstacle Recognition and Ranging Method in Farmland Based on Improved YOLOv8

Unmanned tractors under ploughing conditions suffer from body tilting, violent shaking and limited hardware resources, which can reduce the detection accuracy of unmanned tractors for field obstacles. We optimize the YOLOv8 model in three aspects: improving the accuracy of detecting tilted obstacles, computational reduction, and adding a visual ranging mechanism. By introducing Funnel ReLU, a self-constructed inclined obstacle dataset, and embedding an SE attention mechanism, these three methods improve detection accuracy. By using MobileNetv2 and Bi FPN, computational reduction, and adding camera ranging instead of LIDAR ranging, the hardware cost is reduced. After completing the model improvement, comparative tests and real-vehicle validation are carried out, and the validation results show that the average detection accuracy of the improved model reaches 98.84% of the mAP value, which is 2.34% higher than that of the original model. The computation amount of the same image is reduced from 2.35 billion floating-point computations to 1.28 billion, which is 45.53% less than the model computation amount. The monitoring frame rate during the movement of the test vehicle reaches 67 FPS, and the model meets the performance requirements of unmanned tractors under normal operating conditions.

Development of a deep Q-learning energy management system for a hybrid electric vehicle

In recent years, Machine Learning (ML) techniques have gained increasing popularity in several fields thanks to their ability to find hidden and complex relationships between data. Their capabilities for solving complex optimization tasks have made them extremely attractive also for the design of the Energy Management System (EMS) of electrified vehicles. Among the plethora of existing techniques, Reinforcement Learning (RL) algorithms have unprecedented potential since they can self-learn by directly interacting with the external environment through a trial-and-error procedure. In this paper, a Deep Q-Learning (DQL) agent, which exploits Deep Neural Networks (DNNs) to map the state-action pair to its value, was trained to reduce the CO2 emissions of a state-of-the-art diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. The proposed methodology was tested on a virtual test rig of the investigated vehicle while operating on a charge-sustaining logic. A sensitivity analysis was performed on the reward to test the capabilities of different penalty functions to improve the fuel economy while guaranteeing the battery charge sustainability. The potential of the proposed control strategy was firstly assessed on the Worldwide harmonized Light-duty vehicles Test Cycle (WLTC) and benchmarked against a Dynamic Programming (DP) optimization to evaluate each reward. Then the best agent was tested on a wide range of type-approval and Read Driving Emission (RDE) scenarios. The results show that the best-performing agent can reach performance close to the DP reference, with a limited gap (7 %) in terms of CO2 emissions.

Scalable evaluation methods for autonomous vehicles

Effective intelligent driving test and evaluation methods can improve the development and deployment process of autonomous vehicles (AVs). However, due to the extreme complexity and high dimensionality of driving behavior, how to objectively and efficiently evaluate the multi-dimensional performance of AVs in simulation and real-world environments is a long-standing problem. This paper proposes an objective multi-dimensional comprehensive evaluation (OMDCE) method that divides the intelligent driving test into four modules: test scenarios, scenario complexity model, simulation test platform, and automated evaluation system. The scenario complexity model is proposed to bridge the gap between the test scenarios and the automated evaluation system, thus enabling adaptive scaling of the evaluation scale for test scenarios with different difficulty levels. Besides, based on the existing four evaluation metrics for ego performance, altruism performance evaluation is first proposed to comprehensively portray AVs’ intelligence degree. The OMDCE method was evaluated by testing two different intelligent driving algorithms and conducting real vehicle testing. The experimental results demonstrated that the OMDCE method can effectively evaluate AVs in various scenarios and quantitatively measure their multi-dimensional performance. The proposed method reduces the subjectivity of manual evaluation and speeds up the evaluation. Moreover, it improves the universality and scalability of the evaluation metrics system.

Development and Characterizations of Fine Pitch Flip-Chip Interconnection Using Silver Sintering

Flip-chip interconnects made of silver are promising candidates to overcome the intrinsic limits of solderbased interconnects and match the demand for increased current densities of high-performance microprocessors. Dipbased interconnects have been demonstrated to be a promising approach to form electrical interconnects by sintering paste between copper pillars and pads. However, the quality of the process is limited by residual porosity and poor performances of the sintered joint formed between the pillar and the pad during sintering if a pressure > 50 MPa is not applied in order to decrease the final porosity. In this study, development has been focused on varying key dipping process parameters allowing a pressureless sintering process. Dip-transfer process was optimized on test vehicle and has shown electrical continuity over 700 interconnections with diameter down to 50 μm. We demonstrate high reliability of the process with microstructural observations, tomography X and thermal cycle up to 200 cycles without breakdown.

Optimized energy management for plug-in hybrid vehicles with predicted driving cycles1

The traditional rule-based energy management strategy for plug-in hybrid vehicles has issues, such as difficulty in online correction and limited online optimization capabilities. In addition, the global optimization energy management strategy cannot be applied online or in real-time. Considering the above difficulties, this study proposes a real-time optimization energy management strategy based on the Markov chain for driving condition prediction and online optimization with the minimum principle. To verify the proposed control strategy, the plug-in hybrid vehicle dynamics model, driving condition prediction model, and online optimization control model were first established. The initial value of the battery state of charge was set to 0.4 under the UDDS (Urban Dynamometer Driving Schedule) standard cycle. The simulation results showed that the comprehensive fuel consumption cost was 1.66 yuan, which was 8.28% better than the energy economy of the traditional rule-based energy management strategy. At the same time, a complete vehicle test was also conducted based on a sample vehicle test platform. The experimental results indicated that the energy management strategy proposed herein exhibits better fuel economy compared to that exhibited by the traditional rule-based energy management strategy. Simulations and experiments have verified the effectiveness of the proposed control strategy in this study.

A model-tuned predictive sliding control approach for steering angle following of full self-driving vehicles

Steer-by-wire is a key technology to realize full self-driving for intelligent vehicles, where this is a challenge for steering angle following accurately. Therefore, a hybrid control thinking is proposed to design a model-tuned predictive sliding control approach, which is utilized to realize angle following of the electric motor steer-by-wire system. Here, sliding mode control is used as a core algorithm to be fit for the dynamics characteristics of the steer-by-wire system. Model tuning control is proposed to update model parameters by a receding horizon method, which means that some posteriori knowledge of the control system is utilized to make the model more accurate. Model predictive control is used to optimize the sliding manifold parameters of sliding mode control, which means that some priori knowledge of the control system is used to make the control law much fitter. Then we discuss a series of studies on the steer-by-wire system model and the control algorithm that, collectively, develop an approach of how the hybrid control algorithm precisely makes the front wheel angles follow desired steering commands. The designed approach has been deployed into a steering control unit, and tested in a steering test vehicle to realize the angle following of the electric motor steer-by-wire system. Based on the experimental results and statistical analysis, it can be concluded that the hybrid control thinking is a good idea of how to fuse several algorithms into a control approach, and the model-tuned predictive sliding control approach is a good candidate for the steering angle following of full self-driving vehicles.

Thermal management improvement in electric vehicles through design optimization of coolant distributor valves

On battery electric vehicles a precise control of heat flows is required for passenger comfort and for both performance and safety of battery packs. This is typically achieved with a thermal management system which employs some type of liquid coolant to transfer heat. Coolant distributor valves are used to regulate coolant flows through the exchangers, for example to recover heat from hot sources, thus to increase vehicle energy efficiency. The development of this type of component is high-priced and the design is generally complex since several operating functions and manufacturing constraints should be satisfied. Despite this complexity and the positive impact such valves have on the thermal management of electric vehicles, a few works are currently available in the literature on design procedures for this component, where only a partial overview of the topic is provided and a comprehensive design methodology considering the effective operating conditions is still missing. In this work we construct a physical model of the valve for torque, internal leakage and pressure drop, and we build an optimization procedure to improve the global performance of the valve. We compare the obtained designs with a simpler approach that optimizes performance parameters independently and we show that designs which severely under-perform with respect to the uncontrolled performance parameters can be produced if an over-simplified design approach is followed. We then show with a global vehicle thermal model that the impact of valve design on global vehicle performance crucially depends on the thermal exchanges at vehicle level and, thus, on its operating conditions. In particular, the impact is considerable when mixing of cold and hot flows through the valve occurs. For a specific example vehicle evaluated in a type-3a cycle of the Worldwide Harmonized Light Vehicle Test Procedure, a valve determined with the proposed optimization procedure allows us to obtain in this condition an increase of about 1 km in the vehicle driving range with respect to a valve defined with the simpler approach.

Reducing Tonal Noise in IPMSM Vehicle Drives Through Harmonic Injection

PMSM drives are widely used in powertrains for hybrid and battery electric vehicles. Tonal noise radiation of the drive results from magnetic force excitations in the air-gap of the machine. As previous work has shown it is possible to reduce magnetic noise by the injection of current harmonics in specific orders. Therefore feed-forward voltage harmonics can be used. The determination of amplitudes and phases on a drive test bench or vehicle test however is a complex and time-consuming task. The paper contributes by giving a framework to identify the necessary orders, amplitudes and phases with the help of detailed machine models. Simulation and measurement results are presented to prove the injection method’s feasibility and to show that multiple orders can be reduced. In result an improved drive control can actively reduce noise without any additional hardware or cost.

Possibilities to evaluate the vehicle’s accelerations through MATLAB Simulink simulations

This scientific present paper explores the methods for assessing the longitudinal and lateral accelerations of a vehicle through the combination of experimental validation and MATLAB Simulink simulations. Comprehending these accelerations is essential for a number of uses, such as stability, overall performance analysis, and vehicle safety. The first step of the study is building a detailed Simulink model of the car. With an emphasis on lateral and longitudinal accelerations, this model makes it easier to simulate a range of driving scenarios and explore how a vehicle handles and behaves under different circumstances. A key element of the study is the experimental validation of the Matlab Simulink model, which involves gathering real-world data from vehicle testing and contrasting it with simulated outcomes. Simulink model iterative refinement is made possible by the integration of simulation and experimentation, which ultimately improves the model’s predictive accuracy. The study’s conclusions demonstrate the integrated approach’s potential to advance vehicle dynamics analysis and make cars safer and more effective. Furthermore, it offers insights into the optimization of vehicle designs and the development of innovative control strategies to enhance overall road safety and vehicle performance.

Numerical analysis and evaluation of a semi-heavy guardrail system

The continuous increase in traffic accidents, following the rise in the number of vehicles in traffic and their speed, requires the development of research on the design of active and passive safety systems. This research mainly aims to compare the performance of commonly used passive safety systems (semi-heavy W-beam guardrails) mounted on roadside and pedestrian bridges to protect vehicles and pedestrians. It is intended to reduce the deformations of the vehicle upon impact with the protective device mounted between the roadside and the pedestrian area for the protection of the vehicle occupants; reduce the parapet working width for the pedestrian’s safety; and maintain the vehicle’s trajectory from the moment of impact to the final movement, between the guardrail and the median axis of the road, to ensure the protection of other road users. A CAD model of the vehicle-guardrail scenario was developed to achieve these objectives. Load simulation cases are performed using the finite element method according to the European standards SR EN 1317 for impact tests of vehicles - TB 42, recommended for semi-heavy guardrails.

Transient aerodynamic behavior of a high-speed Maglev train in plate braking under crosswind

The test speed of high-speed maglev trains (HSMT) exceeds 600 km/h, requiring higher braking performance and technology. Plate braking technology, which is a suitable choice, has been applied for engineering the high-speed test vehicles. However, the unsteady aerodynamic response during the opening process of HSMT under crosswind needs to be studied. This study explores the unsteady aerodynamic characteristics of a HSMT with a train speed of 600 km/h during plate braking at different crosswind speeds. The plate motion is achieved based on the dynamic grid technology, and the unsteady flow field around the train is simulated using the unsteady Reynolds time averaged equation and the shear stress transport k-omega (SST k–ω) turbulence model. This calculation method was verified using wind tunnel test data. The peak aerodynamic drag (AD) of the braking plates overshot during opening. Under a crosswind of 20 m/s, the AD peak of the first braking plate was 11% larger than that without crosswind. The middle braking plates were significantly affected by upstream vortex shedding, and the AD fluctuation was the most severe. The AD of the head and tail coaches is significantly affected by crosswind. With an increase in the crosswind speed, the AD of the head and tail coaches decreased and increased, respectively. Compared with no crosswind, under a crosswind of 20 m/s, the AD of the head coach decreased by 43%, and the AD of the tail coach increased by a factor of approximately 1.1 times. Furthermore, the AD fluctuation of the tail coach was the most severe.

EVALUATION THE STRUCTURE EFFICIENCY OF TESTING EQUIPMENT FOR MANUFACTURE OF AUTOMOBILES

Nowadays, the automotive industry plays a significant role in the structure of domestic me- chanical engineering. There are a large number of enterprises engaged in the production and assembly of cars and trucks of various well-known brands on the territory of our country. A necessary stage in the pro- duction line of automobiles is testing (diagnostics). To diagnose the flow of produced cars, various options for placing technological equipment can be used. In this article, the authors have conducted a study of sev- eral layouts of diagnostic equipment for testing vehicles according to the criterion of the highest throughput using the method of mathematical modeling. As the research results have shown the most efficient equip- ment layout corresponds to the organization of the technological process with a six-post two-beam line. This variant of the organization of the technological process makes it possible to increase the efficiency of the di- agnostic line by almost 2 times. The results of the investigations can be applied to the effective organization of the process of testing automobiles at the enterprises for the production of transport equipment.

Next Level of 1/1 μm Line and Space Copper Redistribution Layer Fabrication with Organic Dielectric Materials

An electrical reliability of fine copper redistribution layer (RDL) with 1/1 μm line and space fabricated by using positive photosensitive polyimide (PSPI) has been demonstrated. The polyimide containing flexible molecular units in PSPI was introduced, in assumption to increase the entanglement of each polymer chain with a design concept of polymer backbone to enhance mechanical and thermal reliability. To conduct a series of tests, test vehicles with semi-additive copper RDL with 1/1 μm line and space were fabricated with Toray’s PSPI for electrical reliability test. Through a series of electrical reliability tests utilizing our test vehicles, PSPI out-performed the phenol-based resin, which has been proven to have excellent mechanical and thermal stabilities when compared with other resins. 1/1 μm line and space electrodes after electrical reliability tests were also observed and cross-sectioned. The observation of electrodes clearly showed oxidation-reduction of the electrodes on anode and cathode, respectively. On the cathode, copper particles of several nm in diameter were formed on the PI film surrounding the copper wiring. On the anode, copper oxide layers of about 100 nm thickness were observed on the copper wiring surface, which turned out to be Cu2O when analyzed with Electron Energy-Loss Spectroscopy (EELS) measurement.

Solder-less Fine Pitch Copper-to-Copper Bonding

The industry has been looking to increase pitch scaling through various methods. One of these methods is an alternative to solid-state solder bonding. However, very few processes can compete with solder bonding’s fast speed, low cost, and flexibility. The approach with the biggest potential for connecting fine pitch interconnects in high-density semiconductor packaging is solder-less copper-to-copper direct bonding. There are many benefits to using copper-to-copper direct bonding, including the ability to achieve ultra-fine-pitch (bump pitch 10 μm), higher reliability (both thermo-mechanically and better electromigration behavior), low resistance, as well as the lack of concern for solder hierarchy for multiple reflow. This copper-to-copper direct bonding technology enables a variety of 2.5D/3D advanced packaging architectures and is also suitable for multi-die stacking. In this study, we report the investigation of a direct copper-to-copper bonding methodology and reliability of the bonded components. Our process differs from common hybrid bonding copper-to-copper techniques, in that it is designed for low volume highly complex products. This technology allows a die-to-die and die-to-wafer process using thermocompression bonding under a deoxidizing vapor flow for direct copper-to-copper bonding. The process does not require high temperature oven annealing and can be done in a normal atmospheric environment. The investigated bonding process is ideal for high power, high thermal, high density 3D stacking and high-speed digital communication applications. We demonstrated the bonding procedure using a test vehicle with 40 μm diameter pillars and 80-μm bump pitch. We investigated the effects of bonding force and evaluated joint reliability. Interconnect/bond strength was determined through destructive shear testing and cross-sectional analysis. A scanning electron microscope was used to inspect and examine the bonded joint quality. Finally, completed assemblies were thermal cycled to evaluate degradation of joint strength under induced stress, and resistance measurements were performed to evaluate the electrical performance of the bonded copper joint.

Using Outlier Control Technology with Feedforward Lithography to Address Die Shifting and Pattern Distortion Challenges in Fan-Out Panel-Level Packaging

Fan-out panel-level packaging (FOPLP) is a packaging technology able to meet the requirements of heterogeneous integration while reducing costs for manufacturers. However, FOPLP faces several significant process challenges. One of these is die shifting, which is a result of the reconstitution process in die-first FOPLP. Pattern distortion is another challenge, one caused by panel deformation in redistribution layer-first FOPLP. These issues cause die and patterns to move away from their nominal positions. If die shifting and pattern distortion are not well addressed during the lithography process, they will result in overlay errors and low overlay yield. Outlier control technology with feedforward lithography is proposed to address these die-shifting and pattern-distortion challenges. Outlier control is based on site-by-site corrections and uses an algorithm to recognize outliers in the substrate, eliminate their negative impacts and optimize overlay corrections to ensure good overlay yield. Additionally, feedforward lithography can further reduce the negative impact to throughput caused by the time lost addressing site-by-site corrections. In this study, we will discuss how die shifting and pattern distortion result in yield and throughput challenges for FOPLP. Then we will demonstrate outlier control technology with feedforward lithography on a test vehicle and how the integration of these two technologies addresses the challenges. We will also review the results of the demonstration and discuss the advantages of this strategy.

Electromigration of Power Devices Part 2: Power Device in Applications in Controlled Environment

In the power semiconductor industry, there is a continuous development toward a higher current capability of devices while device’s dimensions shrink. Although higher current is preferred, the reliability risk of the electromigration (EM) remains challenging. In the present study, a special EM test vehicle is used to investigate the pure EM behavior of power device, following our previous work. The selection of the test condition is discussed in detail, which is defined based on the temperature and current profiles of the device in the actual application, focusing on the applications of the power devices in a controlled environment, i.e., data centers or telecommunication servers. The current and temperature profiles of the device are discussed based on the device’s maximum power dissipation and its respective thermal design. The results show that the different combinations of currents and temperatures can lead to different ratios of acceleration factor between the temperature and the current. Consequently, an inappropriate selection of the testing condition can result in the over-domination of temperature over the current, leading to wrong conclusions. The effects of the PCB surface finish (both Ni and Sn plating) as well as different electron flow directions on the EM were studied. It is concluded that the maximum current that can be applied to a power device in the application within a controlled environment is rather limited by the cooling capability of the system than the EM induced device failure.

Attitude and heading measurement based on adaptive complementary Kalman filter for PS/MIMU integrated system.

The bionic polarization sensor (PS)/MEMS inertial measurement unit (MIMU) integrated system can provide reliable attitude and heading information for unmanned vehicles in the case of GNSS rejection. However, the existing measurement methods have poor adaptability to inclining, sheltering, and other harsh environments, and do not make full use of the complementary characteristics of the gyroscopes, accelerometers, and PS, which seriously affects the system performance. Therefore, this paper proposes an attitude and heading measurement method based on an adaptive complementary Kalman filter (ACKF), which corrects the gyroscopes according to the gravity measured by the accelerometers to improve the attitude accuracy and fuses the IMU heading and tilt-compensated polarization heading by Kalman optimal estimation. On this basis, the maximum correlation entropy of the measured gravity and the theoretical gravity is used to construct an adaptive factor to realize the adaptive complementary of the gyroscopes and the accelerometers. Finally, the effectiveness of the method is verified by the outdoor rotation test without occlusion and the vehicle test with occlusion. Compared with the traditional Kalman filter, the pitch, roll, and heading RMSE of the vehicle test are reduced by 89.3%, 93.2% and, 9.6% respectively, which verifies the great advantages.