Sustainability Files :
Panasonic Wins the Minister's Prize for its Investment-free Energy-saving Method

The Kasai Division, located in Hyogo Prefecture, produces prismatic lithium-ion batteries that are mounted on hybrid and electric vehicles. In recent years, due to production increase to address the expansion of demand for these types of cars, energy consumed in the factory has been on the rise. Despite the promotion of the so-called "METAGEJI (meters and gauges)" approach, where energy consumption is made visible by using meters and gauges as part of reduction measures, coming up with fresh ideas for making further improvements had become difficult.

At the Kasai Division, air-conditioning equipment accounted for more than one-third of the energy consumption in FY2013. With the METAGEJI approach, the temperature and humidity of outdoor air, supplied air, and room air, the inverter frequency of air-conditioning equipment, and other elements were measured and recorded at the time. However, such data was not effectively incorporated when examining measures to improve equipment performance and efficiency, and therefore, the data was not fully leveraged. It was also difficult to identify losses caused by inadequate adjustments of air-conditioning equipment.

Further, in order to implement energy-saving measures at an around-the-clock factory, it was imperative to define the conditions in advance to achieve the optimal operation of air-conditioning equipment and bring out its best efficiency and performance, and to visualize the effects. Therefore, the Kasai Production Group of the Kasai Division set a direction whereby it would calculate the data necessary for examining energy-saving measures and simulate their effects by adopting a statistical approach.

Project team members immediately started the examination of data calculation methods. In order to examine measures to enhance the efficiency of air-conditioning equipment, it is crucial to have data including the maximum water vapor content in the air (saturated water vapor pressure), water vapor content in 1 m³ of air (absolute humidity), heat quantity in the air (specific enthalpy), and temperature at which the dew condensation of outdoor air that has been introduced begins (dew-point temperature). In general, these data are derived from temperature and humidity conditions by using a chart called psychrometric diagram. However, it is practically impossible to monitor hourly, daily, monthly, and yearly trends through manual calculation while adjusting temperature and humidity conditions. Therefore, the members came up with the idea of entering an arithmetic expression for the psychrometric diagram in a PC spreadsheet to automatically calculate the data.

A variety of formulas for calculating data are available thanks to many research cases. However, there were issues associated with their use in the spreadsheet such as "two formulas must be used according to different purposes" or "the formula is too complex." Team members decided on the policy to develop an original arithmetic expression that is as simple and versatile as possible by referencing existing formulas. They underwent the process of trial and error, during which they put their heads together and repeatedly held discussions for more than a month, and each member spent their spare time conducting verifications.

These initiatives eventually bore fruit. They were able to establish an arithmetic expression that generates fewer errors in comparison to the values of the psychrometric diagram and actual measurement values of air-conditioning equipment in operation.

Taking advantage of this arithmetic expression, the team members conducted simulations aiming to improve the efficiency of air-conditioning equipment.

A desiccant air-conditioner is one of the successful energy-saving cases. It is a device that makes outdoor air flow through cold water, and following the dew condensation and dehumidification processes, dry air is generated by applying dehumidifying agent. Based on the arithmetic expression, the members simulated the relationship between energy consumed in each process and the dehumidification amount and found that optimal energy-saving operation is achieved when cold water conventionally set to 16°C was set to 12°C. In FY2014, the use of this expression helped reduce energy consumption equivalent to 83.5 kl of crude oil compared to the previous year.

An outdoor air processing air-conditioner is another typical example, which cools outdoor air, and following the dew condensation and dehumidification processes, reheats the air to supply it throughout the factory. Team members simulated in-factory temperature and humidity conditions while taking account of room temperature increase due to heat radiated by production equipment. As a result, they came to the conclusion that an indoor environment can be maintained as before, even when the average temperature of the air supplied is reduced from the conventional 23°C to 20°C. The use of the expression contributed to the achievement of a reduction of energy consumption equivalent to 240.7 kl of crude oil compared to the previous year.

Some lithium-ion battery production processes require the strict control of temperature and humidity conditions for quality assurance purposes. Team members made a proposal to the production division in which they stated that temperature and humidity conditions can be maintained as before even if the settings of air-conditioning equipment are changed, and also presented the anticipated energy-saving and cost reduction effects. Consensus building with the frontlines played a crucial part in achieving the acceleration of activities and maximization of effects.

Through the implementation of a series of measures, the Kasai Division achieved a reduction of energy consumption equivalent to 690.7 kl of crude oil and curtailed CO₂ emissions by 1,356.8 tons compared to the previous year, without making any investments in air-conditioning equipment or measuring instruments. This know-how is now being applied to other factories. The division is anticipating the expansion of energy-saving and CO₂ reduction effects in the future by pursuing the optimized control of air-conditioning equipment.