Doing more with less

Better control of electrified powertrains using predictive software can deliver even greater efficiency gains in hybrid vehicles

No driver wants their vehicle to waste fuel unnecessarily as that is money down the drain. Equally, the thought of an engine burning more fuel than it needs to, releasing more harmful gases into the atmosphere than it should, is a scenario no one would actively seek out.

These sentiments may seem obvious but they are reminders that fuel-efficient vehicles appeal to all: drivers, regulators and the wider society. Electrification, and specifically hybridisation, is allowing OEMs to provide similar or higher levels of vehicle functionality with less use of fuel. But Denso believes that even these fuel-efficient powertrains can be improved.

Kenzo Yano, the firm’s head of European engineering, said: “While many of the hardware and component-related efficiency improvements (such as better electric motors and batteries) result in additional unit costs, software approaches come nearly at zero additional unit costs – higher development costs are allocated on all sold units and are therefore rather marginal.

“Many of today’s software improvements target improving the vehicle’s operation strategy in terms of driveability, fuel consumption, emissions and NVH, and are often rule-based and non-predictive.

“As a result, the fuel consumption reduction is only as good as the degree of the assumptions’ accuracy compared to the actual and individual driving behaviour.”

The Tier One has been looking at an alternative application of upgrading the operational software, with a view to being more predictive about driving conditions.

In the summer of 2013, Denso and development firm FEV, jointly set up a project called City-e, which aimed to connect existing and new solutions to develop a path towards a smart and mobile society tailored to the requirements of European drivers.

Predictive pay-off

The key objective of the project was to develop intelligent, electrified powertrain technologies that, with the use of sensors and maps, have predictive functionalities that could reduce fuel consumption and CO2 emissions, as well as improve safety, driving dynamics and comfort.

Using model-in-the-loop simulation tools helped to shorten development time, with Yano and his team devising a predictive control strategy for hybrid systems.

tags: June 2016 Denso Electronics
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