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This paper presents a novel torque distribution strategy (TDS) and a modified regenerative braking strategy (MRBS) for distributed-drive electric vehicle (DDEV) considering energy saving and brake stability. The presented TDS minimizes the energy consumption from battery in driving process. In order to overcome the shortcomings by using polynomial approximation for motor efficiency and the local minima problem, an exhaustive search method (ESM) is proposed to obtain the optimal front-rear torque distribution ratio. First, the power summation of four in-wheel motors is selected as the cost function of the optimization problem. Second, the ESM is designed to obtain the optimal torque distribution ratio according to current torque demand and motor speed based on motor efficiency map. Maximum motor torque and tire-road conditions are taken as constraints. Third, a MRBS is proposed to improve energy recovery performance by take ECE R13 and motor efficiency into account.

Gearbox fault diagnosis is one of the core research areas in the field of rotating machinery condition monitoring. The signal processing-based bearing fault diagnosis in the gearbox is considered as challenging as the vibration signals collected from acceleration transducers are, in general, a mixture of signals originating from an unknown number of sources, i.e. an underdetermined blind source separation (UBSS) problem. In this study, an effective UBSS-based algorithm solution, that combines empirical mode decomposition (EMD) and kernel independent component analysis (KICA) method, is proposed to address the technical challenge. Firstly, the nonlinear mixture signals are decomposed into a set of intrinsic mode function components (IMFs) by the EMD method, which can be combined with the original observed signals to reconstruct new observed signals. Thus, the original problem can be effectively transformed into over-determined BSS problem.

In order to reflect the actual power consumption of logistics electric vehicles in a city, sample real vehicle road data. After preprocessing, the short-stroke analysis method is used to divide it into working blocks of no less than 20 seconds. Based on principal component analysis, three of the 12 characteristic parameters were selected as the most expressive. K-means clustering algorithm is adopted to obtain the proportions of various short strokes, according to the proportion, select the short stroke with small deviation degree to combine, and construct the driving cycle, it has the characteristics of low average speed, high idle speed ratio and short driving distance. AVL-cruise software builds the vehicle model and runs the driving cycle of urban logistic EV. Compared with WLTC, the difference in power consumption is 34.3%, which is closer to the actual power consumption, the areas with the highest motor speed utilization are concentrated only in the idle area.

As a global optimization method, dynamic programming (DP) can be employed to seek the optimal velocity with minimum energy consumption for EV on given driving cycles. Due to its terrible computational burden, conventional DP is not suitable for real-time implementation especially with higher dimensions. In this paper, we propose an iterative dynamic programming (IDP) approach to reduce computing time firstly. The IDP can obtain the optimal control laws alike the conventional DP by converging the optimal control strategy iteratively and save considerable computing time. Second, the developed IDP and model predictive control (MPC) are combined to establish a real-time cruising controller called IDP-MPC for an EV with terrain preview. In the predictive controller, we use the IDP to solve a constrained finite horizon nonlinear optimization problem.

The design of aluminum foam reinforced thin-walled tubes has garnered much interest recently due to the high energy absorption capacity of these tubes. As a new kind of engineering composite material, aluminum foam can hugely increase the crashworthiness capacity without sacrificing too much weight. In this paper, axisymmetric thin-walled hollow tubes with four different kinds of cross-sections (circular, square, hexagonal and octagonal) are studied to assess their performance for crashworthiness problems. It is found that the tube with square cross-section has the best crashworthiness performance under axial impact. To seek optimal designs of square aluminum foam reinforced thin-walled tubes, a surrogate modeling technique coupled with a multi-criteria particle swarm optimization algorithm has been developed, to maximize specific energy absorption (SEA) and minimize peak crash force (PCF).

Due to the high center of gravity of medium-duty vehicles, rollover accidents can easily occur during high-speed cornering and lane changes. In order to prevent the deformation of the body structure, which would restrict the survival space and cause compression injuries to occupants, it is necessary to investigate methods for mitigating these incidents. This paper establishes a numerical model of right-side rollover for a commercial medium-duty vehicle in accordance with ECE R66 regulations, and the accuracy of the model is verified by experiment. According to the results, the material and size parameters of the key components of the right side pillar are selected as design variables. The response result matrix was constructed using the orthogonal design method for total mass, energy absorption, maximum collision acceleration, and minimum distance from the survival space.

In this paper, for the front wall of a certain automobile, the defects of drawing splits, excessive thinning and excessive springback in the sheet metal forming process are analyzed and predicted. The stamping process has been simulated. The influence of different technical parameters (blank holder force, stamping speed, die gap and friction coefficient) on the forming results was further investigated using the center composite experiment. Through preliminary finite element simulation, the main drawing defects and trimming springback were analyzed. The second-order response surface model was established to perform the multi-objective optimization design of the stamping process with a NGSA-II genetic algorithm. Based on the relevant simulation data, multiple springback compensations are performed on the die surface to reduce the final springback of the part to meet the requirements.

In this advanced technological era, lightweight design for fuel efficiency and environmental friendliness is essential for both conventional and hybrid electric vehicles (HEVs), without sacrificing the durability which is an important design factor for vehicle safety. To achieve these objectives, reduction of the structural mass of the full vehicle plays a vital role. The scope of this paper is to describe design methodologies for the vehicle differential case applied to achieve light weight and to ensure product life. The focus of this paper includes two tasks. The topology optimization and fatigue analysis of a vehicle differential case are conducted. Finite element analysis (FEA) is used to simulate the stress with constraint. After that, optimization parameters (design variables, responses, objective functions and constraints) of a vehicle differential case are selected for lightweight design by solid isotropic microstructures with penalization (SIMP) method.