Functional Firmware and Control Systems

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With no internal firmware expertise, I was challenged to adapt my skillset to take control of this aspect of the project. This was only natural given I already was responsible for the performance sub-system of the product which were inherently coupled areas. 

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Performance Philosophy

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To have a North Star goal when making decisions in product development, I wated to propose a central aim for this product. This resulted in the core goal of the control system being simple in principle but challenging in practice:

A user should only need to put a pizza into the oven and remove it at the right time to receive a perfectly cooked result.

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At the same time, the product had to satisfy two competing user groups:

1. Beginner users entering the world of high-temperature pizza cooking.

2. Expert users and professional chefs demanding full control and high-performance Neapolitan capability.

 

This required designing a system capable of both highly automated cooking and manual control flexibility. One of the biggest challenges was ensuring these goals were satisfied whilst keeping the UI simple which is why I ended up with the responsibility of UI design. 

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Adaptive Cooking System- Pizza Intelligence™

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I designed the firmware architecture behind the oven’s adaptive cooking system, released as the patent-pending Pizza Intelligence™ feature. The system senses when a pizza is in the oven and manages the cooking output based on the pizza style and live temperature data. 

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Each pizza preset required tuning multiple parameters including stone temperature targets, air temperature limits, element power distribution and balance and cook timing profiles.​ These parameters were developed through extensive empirical testing, involving hundreds of pizzas cooked (and, of course, eaten) under controlled conditions to characterise thermal behaviour and optimise performance.

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Control Systems

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Several distinct control systems were implemented for the Pizza Intelligence: A dynamic system controlling top and bottom heating elements to maintain a stable stone temperature while managing radiant heat balance for topping browning; conventional oven and grill modes in which separate firmware logic was developed to allow traditional oven functionality including roasting, baking and grilling, operating across a wide temperature range; and dough proofing mode - an ultra-low temperature control mode capable of maintaining temperatures as low as 20 °C, enabling precise, controlled dough fermentation or rapid defrosting. All of these modes required a separate control approach due to the very varied levels of thermal output relative to the oven’s heating capability.

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Building all of these different control systems into a fundamentally slow-responding, heavily damped thermal system required precise temperature measurement.

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Temperature Measurement and Thermal State Estimation

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One of the most technically demanding challenges was accurate measurement of stone temperature.

The pizza stone is a large thermal mass, resulting in extremely slow dynamic response to system changes such as:

• heating element duty cycles

• air temperature fluctuations

• door opening

• food loading

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The hardware sensing architecture imposed additional constraints:

• a single high-temperature food-safe thermocouple

• indirect thermal coupling to the stone

• user-removable stone requiring mechanical tolerance

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Following a late-stage insulation redesign, the thermocouple was no longer optimal for the new thermal system - yet another case study begging for further up-front development work and understanding before committing to tooling to early.

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To solve this, I developed a temperature estimation algorithm that maps measured thermocouple readings to the estimated stone temperature.

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The algorithm incorporated:

• transient thermal compensation

• heating element state modelling

• mathematically modelled system derived correction functions

• safety-bounded estimation logic

• Continuity checks

As well as some novel control system approaches. 

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This approach allowed the system to maintain accurate control of the true cooking surface temperature despite indirect sensing.

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Because the algorithm directly influenced safety-critical heating behaviour, it required extremely rigorous validation across not just normal cooking conditions but also misuse scenarios, sensor faults, edge-case thermal states etc. It required a deep understanding of thermodynamics, user interaction and of course the firmware itself. Control logic had to be optimised for performance and mitigate against user error or product faults. This meant comprehensive verification test plans had to be made and carried out

User Interface Firmware Development

 

A key challenge was translating the complexity of the thermal control system into a simple and intuitive user experience.

The UI firmware had to expose:

• multiple cooking modes

• preset pizza styles

• manual temperature control

• custom user presets

• timers and cook notifications

while maintaining an interface that remained approachable for novice users.

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Many final UI behaviour decisions were made during on-site development at the manufacturing partner in China, where rapid iteration and real-time testing were required to meet project deadlines.

The resulting system allows users to quickly select a pizza style and begin cooking immediately, while still offering deeper control for experienced users.

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Being so intimately involved in the UI and control logic meant that I was dragged into many category management and product strategy meetings since I was mainly responsible for defining what the oven was and what it did and for whom.