Mechanical Engineering

The environment encompassing the automotive industry is rapidly changing with the diversification of power sources intended to achieve carbon neutrality and the need for compatibility with new mobility services as represented by MaaS*1. Accordingly, the mechanical systems in automobiles are becoming increasingly sophisticated and complex, giving rise to the demand to simultaneously achieve different types of performance, such as downsizing, higher efficiency, comfort, and resource-savings. We will create new added-value for Toyota Group’s core products by expanding its basic technologies of mechanical engineering with a focus on structures, mechanisms, heat and fluid flows, and lubrication, and by promoting digital twin research based on the experimental measurement and simulation. Similarly, we will engage in the creation of system-level design, as well as new theories, through strategic collaborating research with other fields for this purpose.
*1 MaaS: Mobility as a Service

Core Technologies

Thermal Engineering, Control and System Engineering, Mechanics of Materials, Design Engineering, Fluid Engineering, Mechanical Elements, Tribology, Dynamics of Machinery and Mechatronics

Data-driven Engine Control

Improving the efficiency of system development is essential for quickly addressing rapid changes in social conditions, which is why data-driven system design methods based on machine learning are expected to serve as a means to achieve this. In order to further enhance control stability without relying on the nature of data, we proposed a method to learn the control object with a specially structured machine learning model. When using this model as a predictor, solutions to mathematical problems that require optimal control under various conditions (optimal control problems) are mathematically guaranteed to be unique and continuous. Currently, we are working to apply the method to engine control in order to achieve smooth control while improving acceleration and environmental performance.*2
*2: Jointly developed in part with Toyota Industries Corporation

Machine learning model for developing highstability control systems

Vibration Reduction based on Wave Modeling

Reducing machine vibration and noise contributes to comfort in mobility and a variety of other living environments, as well as to product safety. We are advancing research into new vibration-damping structures and materials that efficiently use material resources to revolutionize silence, and into their design theories. For example, by deriving equations for the propagation characteristics of elastic waves inside shell architectures with periodic structures, we enabled the design of bandgap periodic structures that do not propagate vibration in specific frequency bands. We applied this method to design a metamaterial structure using a pulp mold*3, and combined the metamaterial bandgap effect with material damping to achieve a vibration-damping component that significantly reduces vehicle vibration and noise over a wider frequency range than before.
*3: Jointly developed with TOYOTA AUTO BODY CO., LTD.

Bandgap design method for periodic structures (top) and application example to a pulp mold (bottom)