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This paper proposes a low-cost but indirect method for occupancy detection and occupant counting purpose in current and future automotive systems. It can serve as either a way to determine the number of occupants riding inside a car or a way to complement the other devices in determining the occupancy. The proposed method is useful for various mobility applications including car rental, fleet management, taxi, car sharing, occupancy in autonomous vehicles, etc. It utilizes existing on-board motion sensor measurements, such as those used in the vehicle stability control function, together with door open and closed status. The vehicle’s motion signature in response to an occupant’s boarding and alighting is first extracted from the motion sensors that measure the responses of the vehicle body. Then the weights of the occupants are estimated by fitting the vehicle responses with a transient vehicle dynamics model.

According to driving scenarios, intelligent vehicle is mainly applied on urban driving, highway driving and close zone driving, etc. As one of the most valuable developments, automated highway driving has great progress. This paper focuses on automated highway driving decision, and considering decision efficiency and feasibility, a hierarchical motion planning algorithm based on dynamic programming was proposed, and simultaneously, road coordinate transformation methods were developed to deal with complex road conditions. At first, all transportation user states are transformed into straight road coordinate to simplify modeling and planning, then a set of candidate paths with Bezier form was developed and with the help of obstacles motion prediction, the feasible target paths with collision-free were remains, and via comparing vehicle performance for feasible path, the optimal driving trajectory was generated.

Noise-vibration-harshness (NVH) design optimization problems have become major concerns in the vehicle product development process. The Body-in-White (BIW) plays an important role in determining the dynamic characteristics of vehicle system during the concept design phase. Finite Element (FE) models are commonly used for vehicle design. However, even though the speed of computers has been increased a lot, the simulation of FE models is still too time-consuming due to the increase in model complexity. For complex systems, like vehicle body structures, the numerous design variables and constraints make the FE simulations based optimization design inefficient. This calls for the development of a systematic and efficient approach that can effectively perform optimization to further improve the NVH performance, while satisfying the stringent design constraints.

The prediction and control of gear vibration and noise has become very important in the design of a quiet, high-quality gearbox systems. The vibratory energy of the gear pair caused by transmission error excitation is transmitted structurally through shaft-bearing-housing assembly and radiates off from exterior housing surface. Most of the previous studies ignore the contribution of components flexibility to the transmission error (TE) and system dynamic responses. In this study, a system level model of axle system with hypoid gear pair is developed, aiming at investigating the effect of the elasticity of the shafts, bearings and housing on TE as well as the contribution of flexible bearings on the dynamic responses. The load distribution results and gear transmission errors are calculated and compared between different assumptions on the boundary conditions.

Due to traffic congestion and environmental pollution, connected automated vehicle (CAV) technologies based on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure communication (V2I) have gained increasing attention from both academia and industry. Connected hybrid electric vehicles (CHEVs) offer great opportunities to reduce vehicular operating costs and emissions. However, in complex traffic scenarios, high-quality real-time energy management of CHEVs remains a technical challenge. To address the challenge, this paper proposes a hierarchical eco-driving strategy that consists of speed planning and energy management layers. At the upper layer, by leveraging the real-time traffic data provided by vehicle-to-everything (V2X) communication, dynamic traffic constraints are predicted by the traffic flow predictor developed based on the Hankel dynamic mode decomposition algorithm (H-DMD).

Due to the design of lightweight, high speed driveline system, the coupled bending and torsional vibration and rotordynamics must be considered to predict vibratory responses more realistically. In the current analysis, a lumped parameter model of the propeller shaft is developed with Timoshenko beam elements, which includes the effect of rotary inertia and shear deformation. The propeller shaft model is then coupled with a hypoid gear pair representation using the component mode synthesis approach. In the proposed formulation, the gyroscopic effect of both the gear and propeller shaft is considered. The simulation results show that the interaction between gear gyroscopic effect and propeller shaft bending flexibility has considerable influence on the gear dynamic mesh responses around bending resonances, whereas the torsional modes still dominate in the overall frequency spectrum.

As a crucial part of the intelligent transportation system, traffic signal control will realize the boundary control of the traffic area, it will also lead to delays and excessive fuel consumption when the vehicle is driving at the intersection. To tackle this challenge, this research provides an optimized control framework based on reinforcement learning method and speed guidance strategy for the connected vehicle network. Prior to entering an intersection, vehicles are focused on in a specific speed guidance area, and important factors like uniform speed, acceleration, deceleration, and parking are optimized. Conclusion, derived from deep reinforcement learning algorithm, the summation of the length of the vehicle’s queue in front of the signal light and the sum of the number of brakes are used as the reward function, and the vehicle information at the intersection is collected in real time through the road detector on the road network.

Road load data is an essential input to evaluate vehicle durability and strength performances. Typically, load case of pothole impact constitutes the major part in the development of structural durability. Meanwhile, misuse conditions like driving over a curb are also indispensable scenarios to complement impact strength of vehicle structures. This paper presents a methodology of establishing Multi-body Dynamics (MBD) full vehicle model in Adams/Car to acquire the road load data for use in durability and strength analysis. Furthermore, load level between durability and misuse conditions of the same Impact road was also investigated to explore the impact due to different driving maneuvers.

The research on coasting resistance is vital to electric vehicles, since the smaller the coasting resistance, the longer the coast-down distance. Vehicle coast resistance consists of rolling resistance, vehicle inner resistance and the aerodynamic drag. The vehicle inner resistance is mainly caused by driveline’s friction loss and oil splash loss. The rolling resistance is decided by tire resistance coefficient, which is influenced by tires and road conditions. And the aerodynamic drag is affected by vehicle’s shape and air. In this paper, four factors including tire pressure, road surface condition, atmosphere temperature, and recirculation on or off are examined. Experimental tests have been conducted on three different vehicles: one subcompact sedan, one compact sedan and one subcompact SUV. Then experimental results have been imported to simulation model to investigate the corresponding influence on NEDC range.

This paper presents a road classifier based on the system response with consideration of the tire enveloping. The aim is to provide an easily applicable yet accurate road classification approach for automotive engineers. For this purpose, tire enveloping effect is firstly modeled based on the flexible roller contact (FRC) theory, then transfer functions between road input and commonly used suspension responses i.e. the sprung mass acceleration, unsprung mass acceleration, and rattle space, are calculated for a quarter vehicle model. The influence of parameter variations, vehicle velocity, and measurement noise on transfer functions are comprehensively analyzed to derive the most suitable system response thereafter. In addition, this paper proposes a vehicle speed correction mechanism to further improve the classification accuracy under complex driving conditions.

The working principle of dual mass flywheel - radial spring (DMF-RS) type torsional vibration damper was analyzed, and the design method of natural torsional vibration characteristics control of DMF-RS type torsional damper for automotive powertrains was studied herein. Based on the multi-freedom lumped mass - torsional vibration spring analysis model of powertrain, the natural torsional vibration characteristics of the system with DMF-RS type torsional damper were analyzed, and compared with the clutch type torsional vibration damper, the effectiveness of DMF-RS type torsional damper on the torsional vibration control was verified.

In order to measure the noise of auto shock absorbers, a test bench used to detect piston-rod vibration responses of shock absorbers and measuring analyzer named SANTS-I were developed. The vibration response data was detected by bench tests, which shows that there are high-frequency violent peaks on the sine curve of piston-rod oscillating with relative low frequency. In order to explain the interior work dynamic mechanism of shock absorbers, a schematic Micro-process Dynamic Model with 10 steps particularly divided extension and compression stroke in more detail, and dynamic differential equations for each step were presented and discussed. Furthermore, numerical simulation for the inner impacts interaction between piston and damping fluid of hydraulic shock absorber was realized by ADINA software, by the establishment of a gas-liquid two-phase finite element model.