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Battery models are often applied to describe the dynamic characteristics of batteries and can be used to predict the state of the battery. Due to the process of charging and discharging, the battery heat generation will cause the inhomogeneity between inner battery temperature and surface temperature. In this paper, a novel battery impedance model, which takes the impact of the battery internal temperature gradient on battery impedance into account, is proposed to improve the battery model performance. Several experiments are designed and conducted for pouch typed battery to investigate the electrochemical impedance spectroscopy (EIS) characteristics with the artificial temperature gradient (using a heating plate). Experimental results indicate that the battery internal temperature gradient will influence battery EIS regularly.

Lightweight automobile has an important role in saving the energy, improving the fuel economy and reducing the exhaust emission. However, reducing the mass of the automobile need to meet the structural and NVH (Noise, Vibration and Harshness) performance requirements. With the rapid development of Computer Aided Engineering (CAE) technology, more and more people tend to research the complex engineering application problem by computer simulation. An important challenge in today's simulation is the Multidisciplinary Design Optimization (MDO) of an automobile, including mass, stiffness and modal etc. This paper presents a MDO study in a minicar hatchback.

The unscented Kalman filter (UKF) is applied to estimate the real vehicle velocity. The velocity estimation algorithm uses lateral acceleration, longitudinal acceleration and yaw rate as inputs. The non-linear vehicle model and Dugoff tire model are built as the estimation model of UKF. Some parameters of Dugoff tire model and vehicle, which can't be measured directly, are identified by the particle swarm optimization (PSO). For the purpose of evaluating the algorithm, the estimation values of UKF are compared with measurements of the Inertial and GPS Navigation system. Besides, the real time property of UKF is tested by xPC Target, which is a real-time software environment from MathWorks. The result of the real vehicle experiment demonstrates the availability of the UKF and PSO in vehicle velocity estimation.

Most of the existing energy management strategies for Extended-Range Electric Vehicles (E-REVs) are heuristic, which restricts coordination between the battery and the Range Extender. This paper presents an instantaneous optimization energy management strategy based on the Minimum Loss Power Algorithm (MLPA) for a fuel cell E-REV. An instantaneous loss power function of power train system is constructed by considering the charge and discharge efficiency of the battery, together with the working efficiency of the fuel cell Range Extender. The battery working mode and operating points of the fuel cell Range Extender are decided by an instantaneous optimization module (an artificial neural network) that aims to minimize the loss power function at each time step.

Off-road trucks, tractors and earth-moving machines are at high risk of accidents involving falling objects or rollovers. Therefore, these machines need proper protective structures to protect operators. This study investigates the crashworthiness optimization of a hydraulic excavator cab roof rail based on an improved bi-directional evolutionary structural optimization (BESO) method considering two different load cases (a lateral quasi-static load and an impact load from the top of cab, respectively). In the crashworthiness optimization problem, a weighted summation of external works done by the two different load cases is treated as the objective function while the volume of design domain is treated as the constraint. A mutative weight scheme is proposed to stabilize the optimization and balance the two load cases. Finite element (FE) model is established and two prototypes are fabricated based on the optimal design.

The mechanical claw is an important functional part of intelligent sanitation vehicles. Its performance significantly influences the functional reliability and structural safety of intelligent sanitation vehicles. The load of the trash changes extensively during the work of the mechanical claw. Hence, a comprehensive consideration of structural uncertainty during designing is needed to meet performance requirements. Uncertainty optimization design should be applied to reduce the sensitivity of structural performance to uncertain factors and ensure the robust performance of the mechanical paw structure. In this study, a numerical model of the mechanical claw of novel intelligent sanitation vehicles is established first in SolidWorks, and a finite element model is built by Optistruct. Based on the analysis of uncertain load factors of the mechanical claw, a robust mathematical model of uncertain factors is established by the Gauss-Chebyshev and Smolyak algorithm.

The nonuniformity property of the temperature field distribution will not only affect on the battery charging and discharging performance but also its lifetime. In this paper the elementary structural design is implemented for Ni-Mh battery package and the corresponding test platform is constructed from the point of view of temperature difference control strategy, the test results show that the present structural design schemes can effectively restrain temperature difference enlargement among the battery stacks. Through the application of adopting the flow field uniformity method to control temperature difference, and flow field optimization inside the battery package, it is found that the flow field velocity change quantity ΔV is gradually reduced as the increase of the afflux hood angle Ak and air vent width Da, and the difference of battery temperature is relatively lower, which denoting that the corresponding relationship can be created based on test data.

As one of the key technologies in autonomous driving, the lateral planning module guides the lateral movement during the driving process. An integrated lateral planning module should consider the non-holonomic constraints of a vehicle, the optimization of the generated trajectory and the applicability to various scenarios. However, the current lateral planning methods can only meet parts of these requirements. In order to satisfy all the performance requirements above, a novel Potential Field (PF) based lateral planning method is proposed in this paper. Firstly, a PF model is built to describe the potential risk of the traffic entities, including the obstacles, road boundaries and lines. The potential fields of these traffic entities are determined by their properties and the traffic regulations. Secondly, the planning algorithm is presented, which comprises three modules: state prediction, state search and trajectory generation.

The past decade has witnessed the rapid development of autonomous parking technology, since it has promising capacity to improve traffic efficiency and reduce the burden on drivers. However, it is prone to the trap of self-centeredness when each vehicle is automated parking in isolation. And it is easy to cause traffic congestion and even chaos when multiple autonomous vehicles require of parking into the same lot. In order to address the multiple vehicle parking problem, we propose a parking planning method with genetic algorithm. Firstly, an optimal mathematic model is established to describe the multiple autonomous vehicle parking problem. Secondly, a genetic algorithm is designed to solve the optimization problem. Thirdly, illustrative examples are developed to verify the parking planner. The performance of the present method indicates its competence in addressing parking multiple autonomous vehicles problem.

In recent years, intelligent driving technology is being extensively studied. This paper proposes a path planning method for perpendicular parking based on vehicle kinematics model using MPC optimization, which aims to solve the perpendicular parking task. Firstly, in the case of any initial position and orientation of the vehicle, judging whether the vehicle can be parked at one step according to the location of the parking place and the width of the lane, and then calculating the starting position for parking, and use the Bezier curve to connect the initial position and the starting position. Secondly, reference parking path is calculated according to the collision constraints of the parking space. Finally, because the parking path based on the vehicle kinematics model is composed of circle arcs and straight lines, the curvature of the path is discontinuous. The reference parking path is optimized using Model Predictive Control (MPC).

Although autonomous valet parking technology can replace the driver to complete the parking operation, it is easy to cause traffic chaos in the case of lacking scheduling for multiple parking agents, especially when multiple cars compete for the same parking slot at the same time. Therefore, in order to ensure orderly traffic and parking safety, it is necessary to allocate parking slots reasonably for multiple autonomous valet parking vehicles. The parking slots allocation model is built as an optimal problem with constraints. Both parking mileage cost and parking difficult cost are considering at the objective function in the optimization problem. There are three types of constraints. The first is the capacity limit of a single parking slot, the second is the space limit occupied by a single vehicle, and the third is the total capacity limit of the parking lot. After establishing parking slots allocation model, the immune algorithm is coded to solve the problem.

The separation and analysis of the torque of the permanent magnet synchronous motor is of great significance for optimizing the torque output of the motor. Based on the frozen permeability method, the virtual work principle (VWP) or the Maxwell stress tensor method (MSTM) is often used to separate the torque for torque analysis. However, considering the influence of non-ideal factors such as motor saturation, cross-coupling and flux harmonics, there are differences in torque separation between the VWP and the MSTM, which has been researched and analyzed in this paper. Based on this, for the assisted airspace barrier design of a surface-inserted permanent magnet synchronous motor, to conduct theoretical research on the torque optimization design, this paper uses the VWP to separate the average torque and the MSTM to separate the torque ripple.

High-powered and modularity is the trend for fuel cell systems. Similar to the evolution from single-cylinder to multi-cylinder in conventional internal combustion engines, fuel cell systems shall also follow this developing process. Compared to single-stack fuel cell systems, multi-stack fuel cell systems (MFCS) can enhance the system maximum output power and improve the system performance. To achieve modular design and improve the performance of high-powered MFCS, a MFCS stacks allocation optimization algorithm based on genetic algorithms is proposed in this paper. First, remaining useful life (RUL) and efficiency are choosing as an integrated optimization index, the decision model for MFCS stacks allocation is developed. Then, a heavy-duty commercial vehicle was used as an example to match the vehicle power train parameters. The genetic algorithm is used to solve the global optimal stacks allocation scheme for the vehicle in a specific application scenario.

Engine compartment thermal management can achieve energy saving and emission reduction. The structural design of the components in the engine compartment affects the thermal fluid flow performance, which in turn affects the thermal management performance. In this paper, based on the phenomenon that the surface of the parts in the engine compartment is abnormally high due to design defects of an SUV engine compartment bottom shield, the engine compartment is modeled and analyzed by CFD using the software STAR-CCM+. It is not conducive to the heat dissipation, so the bottom shield needs to be redesigned. To redesign the shape of the bottom shield, four dimensions and one coordinate value were selected as the design parameters, and the oil pan maximum surface temperature was selected as the optimization target. The Latin hypercube sampling method was used to sample the space uniformly, and the experimental design plan was constructed and simulated.

Improving the heat dissipation performance of the engine radiator in the real working environment is of great significance to the cooling of the engines. The purpose of this paper is to study the influence of the radiator’s geometric parameters on its heat dissipation performance in the cooling module environment and optimize the geometric parameters to improve the heat dissipation performance of the radiator. Based on the performance data obtained from relevant component tests and the engine thermal balance test, the simulation model of the engine thermal management system is established, and the reliability of the model is verified. The heat dissipation performances of the single radiator and the radiator in the cooling module are compared by using the validated model.

The layout of component in the engine compartment affects the fluid flow performance, thereby affects the thermal management performance. Based on the fluid flow performance in the engine compartment of an SUV, this paper proposes local optimization plans of the cooling module—moving downward the oil cooler and forward the intercooler, tilting an angle of the cooling module and shifting the fan. This paper took the fan center temperature as the optimization goal and set three levels for the four factors. It was found that the deviation of the fan has the most significant impact on fan center temperature among four factors. Then we discovered that the interaction between the factors has a significant impact on the air intake volume of the cooling module.

In this paper, an equivalent conversion method is proposed to apply the six-dimensional force road spectrum of the four-axle vehicle on the same platform to the three-axle through the axle load comparison. Further, the feasibility of the devolved equivalent conversion method is verified, and the fatigue performance improvement of the wishbone support structure of a commercial vehicle is finally achieved. Specifically, firstly, the load spectrum at each attachment point of the suspension for the three-axle vehicle is obtained through the iteration of the multi-body dynamic model. Furthermore, the finite element model of the suspension for the three-axle vehicle is established; the analysis of fatigue life for the suspension structure is performed by extracting stress amplitude through the multi-axis cyclic counting method and calculating equivalent force amplitude through McDiarmid’s criterion, combined with the SN curve of the material.

Optimization design of hard point parameters for hinge mechanism has been paid more attention in recent years, attributable to their significant improvement in dynamic performance. In this paper, the experimental analysis and dynamic optimization design of hinge mechanism is performed. The acceleration measurement experiments are carried out at different arrangement points and under different working conditions. Furthermore, the accuracy of established multi-body dynamics model is verified by three-axis accelerometer measurement experiment. In addition, sensitivity analysis for electric strut and gas strut coordinates is performed and shows that the Y coordinate of the lower end point of the electric strut is the design variable that has the greatest impact on the responses.

The driver monitoring system (DMS) plays an essential role in reducing traffic accidents caused by human errors due to driver distraction and fatigue. The vision-based DMS has been the most widely used because of its advantages of non-contact and high recognition accuracy. However, the traditional RGB camera-based DMS has poor recognition accuracy under complex lighting conditions, while the IR-based DMS has a high cost. In order to improve the recognition accuracy of conventional RGB camera-based DMS under complicated illumination conditions, this paper proposes a lightweight low-illumination image enhancement network inspired by the Retinex theory. The lightweight aspect of the network structure is realized by introducing a pixel-wise adjustment function. In addition, the optimization bottleneck problem is solved by introducing the shortcut mechanism.

Aiming at the laborious process in motor structure modeling for acoustic noise calculation, an improved stator structure modeling scheme is proposed, which includes stator structure simplification and equivalent material parameters identification. The stator assembly is modeled as a homogeneous solid with the same size as the stator core, and the influence of model simplification is compensated by orthotropic equivalent material parameters. The equivalent material parameters are acquired through an optimization algorithm by minimizing the error between FEM calculated modal frequencies and the modal tested results. With the stator assembly model, the motor assembly model is built, and the constrained modal characteristics of the motor assembly are verified by comparing the modal frequencies to the resonance bands in the vibration acceleration spectrum. Finally, the motor structure model is used to calculate the electromagnetic noise of an induction motor.