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Problems associated with the inadequacy of energy systems to meet modern needs cause bottlenecks and consequently the loss of energy. One of them is the insufficient thermal load capacity of power lines on every level. From the main electrical circuit, the highest-voltage lines to the 1.5 kV lines can deliver electricity to the immediate vicinity of the end user. The number of electric car users has increased along with the need for more consumption of electricity which will inevitably add strain on the infrastructure of transmission. Energy is unevenly generated by wind farms and solar power plants throughout the day. In order to enjoy the benefits of clean energy generation at night and on windless days, energy must be stored. However, these are processes that are also energy-intensive. The need for the optimisation of energy consumption is unfortunately still not a priority.

A great deal can be achieved in the automotive industry by implementing advanced energy-saving technologies. Firstly, attention should be paid to the recognition of the actual situation, by determining energy consumption in real-time of the entire factory and additionally of each machine and production line. This can be achieved by installing sophisticated measuring systems connected through network that allows data transmission. In many cases, machines and their components are factory-equipped with an energy-measuring mechanism, which has to be configured according to the needs of the production process.

The data analysis in gathering information on the state of the power grid load of machines can be measurably achieved in this way and lead to financial savings. This allows the relationship between loss of energy and specific machine operating parameters or configuration to be established. Savings can often be made by relatively simple optimisation of parameters without the need to rebuild machines. The improvement in the precision of diagnosis in order to effect positive changes, the information collected can be expanded to include environmental conditions: temperature, humidity, sunshine and centre precipitation.

For traditional analytical methods cause-and-effect relationships can be elusive, so tools using artificial intelligence are a good solution. A broad set of innovative, proven technologies, as developed by Mitsubishi Electric, may help in the saving of energy. State of the art motors, servo drives, inverters and energy consumption meters, along with ICONIC SCADA class software and data analysis software packages using AI such as MELSOFT MaiLab and EcoAdviser.

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