Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

Reconfigurable mechanisms can deliberately reconfigure themselves by rearranging the connectivity of components to meet the different requirements of tasks. Metamorphic and origami-derived mechanisms are two kinds of typical reconfigurable mechanisms, which have attracted increasing attention in the field of mechanisms since they were proposed. Improving the independent design level, innovation, and international competitive powers of reconfigurable mechanical products is important. Summarizing related significant innovation research and application achievements periodically will shed light on research directions and promote academic exchanges. This paper presents an overview of recent developments in innovation design of reconfigurable mechanisms in China, including metamorphic and origami mechanisms and their typical applications. The future development trends are analyzed and forecasted.

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

In this paper, an uncertainty propagation analysis method is developed based on an extended sparse grid technique and maximum entropy principle, aiming at improving the solving accuracy of the high-order moments and hence the fitting accuracy of the probability density function (PDF) of the system response. The proposed method incorporates the extended Gauss integration into the uncertainty propagation analysis. Moreover, assisted by the Rosenblatt transformation, the various types of extended integration points are transformed into the extended Gauss-Hermite integration points, which makes the method suitable for any type of continuous distribution. Subsequently, within the sparse grid numerical integration framework, the statistical moments of the system response are obtained based on the transformed points. Furthermore, based on the maximum entropy principle, the obtained first four-order statistical moments are used to fit the PDF of the system response. Finally, three numerical examples are investigated to demonstrate the effectiveness of the proposed method, which includes two mathematical problems with explicit expressions and an engineering application with a black-box model.

Batteries have been widely applied in many high-power applications, such as electric vehicles (EVs) and hybrid electric vehicles, where a suitable battery management system (BMS) is vital in ensuring safe and reliable operation of batteries. This paper aims to give a brief review on several key technologies of BMS, including battery modelling, state estimation and battery charging. First, popular battery types used in EVs are surveyed, followed by the introduction of key technologies used in BMS. Various battery models, including the electric model, thermal model and coupled electro-thermal model are reviewed. Then, battery state estimations for the state of charge, state of health and internal temperature are comprehensively surveyed. Finally, several key and traditional battery charging approaches with associated optimization methods are discussed.

This paper models and optimizes an air-based battery thermal management system (BTMS) in a battery module with 36 battery lithium-ion cells. A design of experiments is performed to study the effects of three key parameters (i.e., mass flow rate of cooling air, heat flux from the battery cell to the cooling air, and passage spacing size) on the battery thermal performance. Three metrics are used to evaluate the BTMS thermal performance, including (i) the maximum temperature in the battery module, (ii) the temperature uniformity in the battery module, and (iii) the pressure drop. It is found that (i) increasing the total mass flow rate may result in a more non-uniform distribution of the passage mass flow rate among passages, and (ii) a large passage spacing size may worsen the temperature uniformity on the battery walls. Optimization is also performed to optimize the passage spacing size. Results show that the maximum temperature difference of the cooling air in passages is reduced from 23.9 to 2.1 K by 91.2%, and the maximum temperature difference among the battery cells is reduced from 25.7 to 6.4 K by 75.1%.

Reliability is important to design innovation. A new product should be not only innovative, but also reliable. For many existing components used in the new product, their reliability will change because the applied loads are different from the ones for which the components are originally designed and manufactured. Then the new reliability must be re-evaluated. The system designers of the new product, however, may not have enough information to perform this task. With a beam problem as a case study, this study explores a feasible way to re-evaluate the component reliability with new loads given the following information: The original reliability of the component with respect to the component loads and the distributions of the new component loads. Physics-based methods are employed to build the equivalent component limit-state function that can predict the component failure under the new loads. Since the information is limited, the re-evaluated component reliability is given by its maxi- mum and minimum values. The case study shows that good accuracy can be obtained even though the new reliability is provided with the aforementioned interval.

In a distributed product realization environment, new paradigms and accompanying software systems are necessary to support the collaborative work of geographically dispersed engineering teams from different disciplines who have different knowledge, experience, tools and resources. To verify the concept of collaboration by separation, we propose a generic information communication medium to enable knowledge representation and exchange between engineering teams, a digital interface. Across digital interfaces, each engineering team maintains its own perspective towards the product realization problem, and each controls a subset of design variables and seeks to maximize its own payoff function subject to individual constraints. Hence, we postulate the use of principles from game theory to model the relationships between engineering teams and facilitate collaborative decision making without causing unnecessary information exchange or iteration across digital interfaces. A product design and manufacturing scenario is introduced to demonstrate the efficacy of using game theory to maintain a clean interface between design and manufacturing teams.

Automobiles evolved from primarily mechanical to electro-mechanical, or mechatronic, vehicles. For example, carburetors have been replaced by fuel injection and air-fuel ratio control, leading to order of magnitude improvements in fuel economy and emissions. Mechatronic systems are pervasive in modern automobiles and represent a synergistic integration of mechanics, electronics and computer science. They are smart systems, whose design is more challenging than the separate design of their mechanical, electronic and computer/control components. In this review paper, two recent methods for the design of mechatronic components are summarized and their applications to problems in automotive control are highlighted. First, the combined design, or co-design, of a smart artifact and its controller is considered. It is shown that the combined design of an artifact and its controller can lead to improved performance compared to sequential design. The coupling between the artifact and controller design problems is quantified, and methods for co-design are presented. The control proxy function method, which provides ease of design as in the sequential approach and approximates the performance of the co-design approach, is highlighted with application to the design of a passive/active automotive suspension. Second, the design for component swapping modularity (CSM) of a distributed controller for a smart product is discussed. CSM is realized by employing distributed controllers residing in networked smart components, with bidirectional communication over the network. Approaches to CSM design are presented, as well as applications of the method to a variable-cam-timing engine, and to enable battery swapping in a plug-in hybrid electric vehicle.

The most advantageous property of magnesium (Mg) alloys is their density, which is lower compared with traditional metallic materials. Mg alloys, considered the lightest metallic structural material among others, have great potential for applications as secondary load components in the transportation and aerospace industries. The fatigue evaluation of Mg alloys under elastic stress amplitudes is very important in ensuring their service safety and reliability. Given their hexagonal close packed structure, the fatigue crack initiation of Mg and its alloys is closely related to the deformation mechanisms of twinning and basal slips. However, for Mg alloys with shrinkage porosities and inclusions, fatigue cracks will preferentially initiate at these defects, remarkably reducing the fatigue lifetime. In this paper, some fundamental aspects about the fatigue crack initiation mechanisms of Mg alloys are reviewed, including the 3 followings: 1) Fatigue crack initiation of as-cast Mg alloys, 2) influence of microstructure on fatigue crack initiation of wrought Mg alloys, and 3) the effect of heat treatment on fatigue initiation mechanisms. Moreover, some unresolved issues and future target on the fatigue crack initiation mechanism of Mg alloys are also described.